Coursera.ipynb

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   "source": [
    "<a href=\"https://www.bigdatauniversity.com\"><img src=\"https://ibm.box.com/shared/static/cw2c7r3o20w9zn8gkecaeyjhgw3xdgbj.png\" width=\"400\" align=\"center\"></a>\n",
    "\n",
    "<h1 align=\"center\"><font size=\"5\">Classification with Python</font></h1>"
   ]
  },
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   "source": [
    "In this notebook we try to practice all the classification algorithms that we learned in this course.\n",
    "\n",
    "We load a dataset using Pandas library, and apply the following algorithms, and find the best one for this specific dataset by accuracy evaluation methods.\n",
    "\n",
    "Lets first load required libraries:"
   ]
  },
  {
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   "source": [
    "import itertools\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.ticker import NullFormatter\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.ticker as ticker\n",
    "from sklearn import preprocessing\n",
    "%matplotlib inline"
   ]
  },
  {
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   },
   "source": [
    "### About dataset"
   ]
  },
  {
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   },
   "source": [
    "This dataset is about past loans. The __Loan_train.csv__ data set includes details of 346 customers whose loan are already paid off or defaulted. It includes following fields:\n",
    "\n",
    "| Field          | Description                                                                           |\n",
    "|----------------|---------------------------------------------------------------------------------------|\n",
    "| Loan_status    | Whether a loan is paid off on in collection                                           |\n",
    "| Principal      | Basic principal loan amount at the                                                    |\n",
    "| Terms          | Origination terms which can be weekly (7 days), biweekly, and monthly payoff schedule |\n",
    "| Effective_date | When the loan got originated and took effects                                         |\n",
    "| Due_date       | Since it’s one-time payoff schedule, each loan has one single due date                |\n",
    "| Age            | Age of applicant                                                                      |\n",
    "| Education      | Education of applicant                                                                |\n",
    "| Gender         | The gender of applicant                                                               |"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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    }
   },
   "source": [
    "Lets download the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
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     "text": [
      "--2019-09-26 16:51:54--  https://s3-api.us-geo.objectstorage.softlayer.net/cf-courses-data/CognitiveClass/ML0101ENv3/labs/loan_train.csv\n",
      "Resolving s3-api.us-geo.objectstorage.softlayer.net (s3-api.us-geo.objectstorage.softlayer.net)... 67.228.254.193\n",
      "Connecting to s3-api.us-geo.objectstorage.softlayer.net (s3-api.us-geo.objectstorage.softlayer.net)|67.228.254.193|:443... connected.\n",
      "HTTP request sent, awaiting response... 200 OK\n",
      "Length: 23101 (23K) [text/csv]\n",
      "Saving to: ‘loan_train.csv’\n",
      "\n",
      "100%[======================================>] 23,101      --.-K/s   in 0.07s   \n",
      "\n",
      "2019-09-26 16:51:54 (304 KB/s) - ‘loan_train.csv’ saved [23101/23101]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "!wget -O loan_train.csv https://s3-api.us-geo.objectstorage.softlayer.net/cf-courses-data/CognitiveClass/ML0101ENv3/labs/loan_train.csv"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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   },
   "source": [
    "### Load Data From CSV File  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Unnamed: 0.1</th>\n",
       "      <th>loan_status</th>\n",
       "      <th>Principal</th>\n",
       "      <th>terms</th>\n",
       "      <th>effective_date</th>\n",
       "      <th>due_date</th>\n",
       "      <th>age</th>\n",
       "      <th>education</th>\n",
       "      <th>Gender</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>PAIDOFF</td>\n",
       "      <td>1000</td>\n",
       "      <td>30</td>\n",
       "      <td>9/8/2016</td>\n",
       "      <td>10/7/2016</td>\n",
       "      <td>45</td>\n",
       "      <td>High School or Below</td>\n",
       "      <td>male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>PAIDOFF</td>\n",
       "      <td>1000</td>\n",
       "      <td>30</td>\n",
       "      <td>9/8/2016</td>\n",
       "      <td>10/7/2016</td>\n",
       "      <td>33</td>\n",
       "      <td>Bechalor</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>PAIDOFF</td>\n",
       "      <td>1000</td>\n",
       "      <td>15</td>\n",
       "      <td>9/8/2016</td>\n",
       "      <td>9/22/2016</td>\n",
       "      <td>27</td>\n",
       "      <td>college</td>\n",
       "      <td>male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>PAIDOFF</td>\n",
       "      <td>1000</td>\n",
       "      <td>30</td>\n",
       "      <td>9/9/2016</td>\n",
       "      <td>10/8/2016</td>\n",
       "      <td>28</td>\n",
       "      <td>college</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>PAIDOFF</td>\n",
       "      <td>1000</td>\n",
       "      <td>30</td>\n",
       "      <td>9/9/2016</td>\n",
       "      <td>10/8/2016</td>\n",
       "      <td>29</td>\n",
       "      <td>college</td>\n",
       "      <td>male</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0  Unnamed: 0.1 loan_status  Principal  terms effective_date  \\\n",
       "0           0             0     PAIDOFF       1000     30       9/8/2016   \n",
       "1           2             2     PAIDOFF       1000     30       9/8/2016   \n",
       "2           3             3     PAIDOFF       1000     15       9/8/2016   \n",
       "3           4             4     PAIDOFF       1000     30       9/9/2016   \n",
       "4           6             6     PAIDOFF       1000     30       9/9/2016   \n",
       "\n",
       "    due_date  age             education  Gender  \n",
       "0  10/7/2016   45  High School or Below    male  \n",
       "1  10/7/2016   33              Bechalor  female  \n",
       "2  9/22/2016   27               college    male  \n",
       "3  10/8/2016   28               college  female  \n",
       "4  10/8/2016   29               college    male  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('loan_train.csv')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(346, 10)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
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   "metadata": {
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   },
   "source": [
    "### Convert to date time object "
   ]
  },
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   "cell_type": "code",
   "execution_count": 5,
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   "outputs": [
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     "data": {
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       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Unnamed: 0.1</th>\n",
       "      <th>loan_status</th>\n",
       "      <th>Principal</th>\n",
       "      <th>terms</th>\n",
       "      <th>effective_date</th>\n",
       "      <th>due_date</th>\n",
       "      <th>age</th>\n",
       "      <th>education</th>\n",
       "      <th>Gender</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>PAIDOFF</td>\n",
       "      <td>1000</td>\n",
       "      <td>30</td>\n",
       "      <td>2016-09-08</td>\n",
       "      <td>2016-10-07</td>\n",
       "      <td>45</td>\n",
       "      <td>High School or Below</td>\n",
       "      <td>male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>PAIDOFF</td>\n",
       "      <td>1000</td>\n",
       "      <td>30</td>\n",
       "      <td>2016-09-08</td>\n",
       "      <td>2016-10-07</td>\n",
       "      <td>33</td>\n",
       "      <td>Bechalor</td>\n",
       "      <td>female</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>PAIDOFF</td>\n",
       "      <td>1000</td>\n",
       "      <td>15</td>\n",
       "      <td>2016-09-08</td>\n",
       "      <td>2016-09-22</td>\n",
       "      <td>27</td>\n",
       "      <td>college</td>\n",
       "      <td>male</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>PAIDOFF</td>\n",
       "      <td>1000</td>\n",
       "      <td>30</td>\n",
       "      <td>2016-09-09</td>\n",
       "      <td>2016-10-08</td>\n",
       "      <td>28</td>\n",
       "      <td>college</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>PAIDOFF</td>\n",
       "      <td>1000</td>\n",
       "      <td>30</td>\n",
       "      <td>2016-09-09</td>\n",
       "      <td>2016-10-08</td>\n",
       "      <td>29</td>\n",
       "      <td>college</td>\n",
       "      <td>male</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0  Unnamed: 0.1 loan_status  Principal  terms effective_date  \\\n",
       "0           0             0     PAIDOFF       1000     30     2016-09-08   \n",
       "1           2             2     PAIDOFF       1000     30     2016-09-08   \n",
       "2           3             3     PAIDOFF       1000     15     2016-09-08   \n",
       "3           4             4     PAIDOFF       1000     30     2016-09-09   \n",
       "4           6             6     PAIDOFF       1000     30     2016-09-09   \n",
       "\n",
       "    due_date  age             education  Gender  \n",
       "0 2016-10-07   45  High School or Below    male  \n",
       "1 2016-10-07   33              Bechalor  female  \n",
       "2 2016-09-22   27               college    male  \n",
       "3 2016-10-08   28               college  female  \n",
       "4 2016-10-08   29               college    male  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['due_date'] = pd.to_datetime(df['due_date'])\n",
    "df['effective_date'] = pd.to_datetime(df['effective_date'])\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "source": [
    "# Data visualization and pre-processing\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "button": false,
    "new_sheet": false,
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    }
   },
   "source": [
    "Let’s see how many of each class is in our data set "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "button": false,
    "new_sheet": false,
    "run_control": {
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   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PAIDOFF       260\n",
       "COLLECTION     86\n",
       "Name: loan_status, dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['loan_status'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "source": [
    "260 people have paid off the loan on time while 86 have gone into collection \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Lets plot some columns to underestand data better:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Solving environment: done\n",
      "\n",
      "## Package Plan ##\n",
      "\n",
      "  environment location: /opt/conda/envs/Python36\n",
      "\n",
      "  added / updated specs: \n",
      "    - seaborn\n",
      "\n",
      "\n",
      "The following packages will be downloaded:\n",
      "\n",
      "    package                    |            build\n",
      "    ---------------------------|-----------------\n",
      "    openssl-1.1.1              |       h7b6447c_0         5.0 MB  anaconda\n",
      "    seaborn-0.9.0              |           py36_0         379 KB  anaconda\n",
      "    ca-certificates-2019.8.28  |                0         132 KB  anaconda\n",
      "    certifi-2019.9.11          |           py36_0         154 KB  anaconda\n",
      "    ------------------------------------------------------------\n",
      "                                           Total:         5.7 MB\n",
      "\n",
      "The following packages will be UPDATED:\n",
      "\n",
      "    ca-certificates: 2019.5.15-1       --> 2019.8.28-0      anaconda\n",
      "    certifi:         2019.6.16-py36_1  --> 2019.9.11-py36_0 anaconda\n",
      "    openssl:         1.1.1d-h7b6447c_1 --> 1.1.1-h7b6447c_0 anaconda\n",
      "    seaborn:         0.9.0-py36_0      --> 0.9.0-py36_0     anaconda\n",
      "\n",
      "\n",
      "Downloading and Extracting Packages\n",
      "openssl-1.1.1        | 5.0 MB    | ##################################### | 100% \n",
      "seaborn-0.9.0        | 379 KB    | ##################################### | 100% \n",
      "ca-certificates-2019 | 132 KB    | ##################################### | 100% \n",
      "certifi-2019.9.11    | 154 KB    | ##################################### | 100% \n",
      "Preparing transaction: done\n",
      "Verifying transaction: done\n",
      "Executing transaction: done\n"
     ]
    }
   ],
   "source": [
    "# notice: installing seaborn might takes a few minutes\n",
    "!conda install -c anaconda seaborn -y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "\n",
    "bins = np.linspace(df.Principal.min(), df.Principal.max(), 10)\n",
    "g = sns.FacetGrid(df, col=\"Gender\", hue=\"loan_status\", palette=\"Set1\", col_wrap=2)\n",
    "g.map(plt.hist, 'Principal', bins=bins, ec=\"k\")\n",
    "\n",
    "g.axes[-1].legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "button": false,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "bins = np.linspace(df.age.min(), df.age.max(), 10)\n",
    "g = sns.FacetGrid(df, col=\"Gender\", hue=\"loan_status\", palette=\"Set1\", col_wrap=2)\n",
    "g.map(plt.hist, 'age', bins=bins, ec=\"k\")\n",
    "\n",
    "g.axes[-1].legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "button": false,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "source": [
    "# Pre-processing:  Feature selection/extraction"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "button": false,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "source": [
    "### Lets look at the day of the week people get the loan "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "button": false,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['dayofweek'] = df['effective_date'].dt.dayofweek\n",
    "bins = np.linspace(df.dayofweek.min(), df.dayofweek.max(), 10)\n",
    "g = sns.FacetGrid(df, col=\"Gender\", hue=\"loan_status\", palette=\"Set1\", col_wrap=2)\n",
    "g.map(plt.hist, 'dayofweek', bins=bins, ec=\"k\")\n",
    "g.axes[-1].legend()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "button": false,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "source": [
    "We see that people who get the loan at the end of the week dont pay it off, so lets use Feature binarization to set a threshold values less then day 4 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "button": false,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Unnamed: 0.1</th>\n",
       "      <th>loan_status</th>\n",
       "      <th>Principal</th>\n",
       "      <th>terms</th>\n",
       "      <th>effective_date</th>\n",
       "      <th>due_date</th>\n",
       "      <th>age</th>\n",
       "      <th>education</th>\n",
       "      <th>Gender</th>\n",
       "      <th>dayofweek</th>\n",
       "      <th>weekend</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>PAIDOFF</td>\n",
       "      <td>1000</td>\n",
       "      <td>30</td>\n",
       "      <td>2016-09-08</td>\n",
       "      <td>2016-10-07</td>\n",
       "      <td>45</td>\n",
       "      <td>High School or Below</td>\n",
       "      <td>male</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>PAIDOFF</td>\n",
       "      <td>1000</td>\n",
       "      <td>30</td>\n",
       "      <td>2016-09-08</td>\n",
       "      <td>2016-10-07</td>\n",
       "      <td>33</td>\n",
       "      <td>Bechalor</td>\n",
       "      <td>female</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>PAIDOFF</td>\n",
       "      <td>1000</td>\n",
       "      <td>15</td>\n",
       "      <td>2016-09-08</td>\n",
       "      <td>2016-09-22</td>\n",
       "      <td>27</td>\n",
       "      <td>college</td>\n",
       "      <td>male</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>PAIDOFF</td>\n",
       "      <td>1000</td>\n",
       "      <td>30</td>\n",
       "      <td>2016-09-09</td>\n",
       "      <td>2016-10-08</td>\n",
       "      <td>28</td>\n",
       "      <td>college</td>\n",
       "      <td>female</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>PAIDOFF</td>\n",
       "      <td>1000</td>\n",
       "      <td>30</td>\n",
       "      <td>2016-09-09</td>\n",
       "      <td>2016-10-08</td>\n",
       "      <td>29</td>\n",
       "      <td>college</td>\n",
       "      <td>male</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0  Unnamed: 0.1 loan_status  Principal  terms effective_date  \\\n",
       "0           0             0     PAIDOFF       1000     30     2016-09-08   \n",
       "1           2             2     PAIDOFF       1000     30     2016-09-08   \n",
       "2           3             3     PAIDOFF       1000     15     2016-09-08   \n",
       "3           4             4     PAIDOFF       1000     30     2016-09-09   \n",
       "4           6             6     PAIDOFF       1000     30     2016-09-09   \n",
       "\n",
       "    due_date  age             education  Gender  dayofweek  weekend  \n",
       "0 2016-10-07   45  High School or Below    male          3        0  \n",
       "1 2016-10-07   33              Bechalor  female          3        0  \n",
       "2 2016-09-22   27               college    male          3        0  \n",
       "3 2016-10-08   28               college  female          4        1  \n",
       "4 2016-10-08   29               college    male          4        1  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['weekend'] = df['dayofweek'].apply(lambda x: 1 if (x>3)  else 0)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "button": false,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "source": [
    "## Convert Categorical features to numerical values"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "button": false,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "source": [
    "Lets look at gender:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "button": false,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Gender  loan_status\n",
       "female  PAIDOFF        0.865385\n",
       "        COLLECTION     0.134615\n",
       "male    PAIDOFF        0.731293\n",
       "        COLLECTION     0.268707\n",
       "Name: loan_status, dtype: float64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby(['Gender'])['loan_status'].value_counts(normalize=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "button": false,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "source": [
    "86 % of female pay there loans while only 73 % of males pay there loan\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "button": false,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "source": [
    "Lets convert male to 0 and female to 1:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "button": false,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Unnamed: 0.1</th>\n",
       "      <th>loan_status</th>\n",
       "      <th>Principal</th>\n",
       "      <th>terms</th>\n",
       "      <th>effective_date</th>\n",
       "      <th>due_date</th>\n",
       "      <th>age</th>\n",
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       "      <th>0</th>\n",
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       "      <td>1000</td>\n",
       "      <td>30</td>\n",
       "      <td>2016-09-08</td>\n",
       "      <td>2016-10-07</td>\n",
       "      <td>45</td>\n",
       "      <td>High School or Below</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
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       "      <td>2</td>\n",
       "      <td>PAIDOFF</td>\n",
       "      <td>1000</td>\n",
       "      <td>30</td>\n",
       "      <td>2016-09-08</td>\n",
       "      <td>2016-10-07</td>\n",
       "      <td>33</td>\n",
       "      <td>Bechalor</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>PAIDOFF</td>\n",
       "      <td>1000</td>\n",
       "      <td>15</td>\n",
       "      <td>2016-09-08</td>\n",
       "      <td>2016-09-22</td>\n",
       "      <td>27</td>\n",
       "      <td>college</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>PAIDOFF</td>\n",
       "      <td>1000</td>\n",
       "      <td>30</td>\n",
       "      <td>2016-09-09</td>\n",
       "      <td>2016-10-08</td>\n",
       "      <td>28</td>\n",
       "      <td>college</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>PAIDOFF</td>\n",
       "      <td>1000</td>\n",
       "      <td>30</td>\n",
       "      <td>2016-09-09</td>\n",
       "      <td>2016-10-08</td>\n",
       "      <td>29</td>\n",
       "      <td>college</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0  Unnamed: 0.1 loan_status  Principal  terms effective_date  \\\n",
       "0           0             0     PAIDOFF       1000     30     2016-09-08   \n",
       "1           2             2     PAIDOFF       1000     30     2016-09-08   \n",
       "2           3             3     PAIDOFF       1000     15     2016-09-08   \n",
       "3           4             4     PAIDOFF       1000     30     2016-09-09   \n",
       "4           6             6     PAIDOFF       1000     30     2016-09-09   \n",
       "\n",
       "    due_date  age             education  Gender  dayofweek  weekend  \n",
       "0 2016-10-07   45  High School or Below       0          3        0  \n",
       "1 2016-10-07   33              Bechalor       1          3        0  \n",
       "2 2016-09-22   27               college       0          3        0  \n",
       "3 2016-10-08   28               college       1          4        1  \n",
       "4 2016-10-08   29               college       0          4        1  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Gender'].replace(to_replace=['male','female'], value=[0,1],inplace=True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "button": false,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "source": [
    "## One Hot Encoding  \n",
    "#### How about education?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "button": false,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "education             loan_status\n",
       "Bechalor              PAIDOFF        0.750000\n",
       "                      COLLECTION     0.250000\n",
       "High School or Below  PAIDOFF        0.741722\n",
       "                      COLLECTION     0.258278\n",
       "Master or Above       COLLECTION     0.500000\n",
       "                      PAIDOFF        0.500000\n",
       "college               PAIDOFF        0.765101\n",
       "                      COLLECTION     0.234899\n",
       "Name: loan_status, dtype: float64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby(['education'])['loan_status'].value_counts(normalize=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "button": false,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "source": [
    "#### Feature befor One Hot Encoding"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "button": false,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Principal</th>\n",
       "      <th>terms</th>\n",
       "      <th>age</th>\n",
       "      <th>Gender</th>\n",
       "      <th>education</th>\n",
       "    </tr>\n",
       "  </thead>\n",
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       "      <th>0</th>\n",
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       "      <td>0</td>\n",
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       "      <th>1</th>\n",
       "      <td>1000</td>\n",
       "      <td>30</td>\n",
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       "      <td>1</td>\n",
       "      <td>Bechalor</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1000</td>\n",
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       "      <td>27</td>\n",
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       "      <td>college</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1000</td>\n",
       "      <td>30</td>\n",
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       "      <td>1</td>\n",
       "      <td>college</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1000</td>\n",
       "      <td>30</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>college</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Principal  terms  age  Gender             education\n",
       "0       1000     30   45       0  High School or Below\n",
       "1       1000     30   33       1              Bechalor\n",
       "2       1000     15   27       0               college\n",
       "3       1000     30   28       1               college\n",
       "4       1000     30   29       0               college"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[['Principal','terms','age','Gender','education']].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "button": false,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "source": [
    "#### Use one hot encoding technique to conver categorical varables to binary variables and append them to the feature Data Frame "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "button": false,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Principal</th>\n",
       "      <th>terms</th>\n",
       "      <th>age</th>\n",
       "      <th>Gender</th>\n",
       "      <th>weekend</th>\n",
       "      <th>Bechalor</th>\n",
       "      <th>High School or Below</th>\n",
       "      <th>college</th>\n",
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       "  <tbody>\n",
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       "      <th>0</th>\n",
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       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
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       "      <th>2</th>\n",
       "      <td>1000</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1000</td>\n",
       "      <td>30</td>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1000</td>\n",
       "      <td>30</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Principal  terms  age  Gender  weekend  Bechalor  High School or Below  \\\n",
       "0       1000     30   45       0        0         0                     1   \n",
       "1       1000     30   33       1        0         1                     0   \n",
       "2       1000     15   27       0        0         0                     0   \n",
       "3       1000     30   28       1        1         0                     0   \n",
       "4       1000     30   29       0        1         0                     0   \n",
       "\n",
       "   college  \n",
       "0        0  \n",
       "1        0  \n",
       "2        1  \n",
       "3        1  \n",
       "4        1  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Feature = df[['Principal','terms','age','Gender','weekend']]\n",
    "Feature = pd.concat([Feature,pd.get_dummies(df['education'])], axis=1)\n",
    "Feature.drop(['Master or Above'], axis = 1,inplace=True)\n",
    "Feature.head()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "button": false,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "source": [
    "### Feature selection"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "button": false,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "source": [
    "Lets defind feature sets, X:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "button": false,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Principal</th>\n",
       "      <th>terms</th>\n",
       "      <th>age</th>\n",
       "      <th>Gender</th>\n",
       "      <th>weekend</th>\n",
       "      <th>Bechalor</th>\n",
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       "      <th>2</th>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1000</td>\n",
       "      <td>30</td>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1000</td>\n",
       "      <td>30</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Principal  terms  age  Gender  weekend  Bechalor  High School or Below  \\\n",
       "0       1000     30   45       0        0         0                     1   \n",
       "1       1000     30   33       1        0         1                     0   \n",
       "2       1000     15   27       0        0         0                     0   \n",
       "3       1000     30   28       1        1         0                     0   \n",
       "4       1000     30   29       0        1         0                     0   \n",
       "\n",
       "   college  \n",
       "0        0  \n",
       "1        0  \n",
       "2        1  \n",
       "3        1  \n",
       "4        1  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X = Feature\n",
    "X[0:5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "button": false,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "source": [
    "What are our lables?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "button": false,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['PAIDOFF', 'PAIDOFF', 'PAIDOFF', 'PAIDOFF', 'PAIDOFF'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y = df['loan_status'].values\n",
    "y[0:5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "button": false,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "source": [
    "## Normalize Data "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "button": false,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "source": [
    "Data Standardization give data zero mean and unit variance (technically should be done after train test split )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "button": false,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/envs/Python36/lib/python3.6/site-packages/sklearn/preprocessing/data.py:645: DataConversionWarning: Data with input dtype uint8, int64 were all converted to float64 by StandardScaler.\n",
      "  return self.partial_fit(X, y)\n",
      "/opt/conda/envs/Python36/lib/python3.6/site-packages/ipykernel/__main__.py:1: DataConversionWarning: Data with input dtype uint8, int64 were all converted to float64 by StandardScaler.\n",
      "  if __name__ == '__main__':\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([[ 0.51578458,  0.92071769,  2.33152555, -0.42056004, -1.20577805,\n",
       "        -0.38170062,  1.13639374, -0.86968108],\n",
       "       [ 0.51578458,  0.92071769,  0.34170148,  2.37778177, -1.20577805,\n",
       "         2.61985426, -0.87997669, -0.86968108],\n",
       "       [ 0.51578458, -0.95911111, -0.65321055, -0.42056004, -1.20577805,\n",
       "        -0.38170062, -0.87997669,  1.14984679],\n",
       "       [ 0.51578458,  0.92071769, -0.48739188,  2.37778177,  0.82934003,\n",
       "        -0.38170062, -0.87997669,  1.14984679],\n",
       "       [ 0.51578458,  0.92071769, -0.3215732 , -0.42056004,  0.82934003,\n",
       "        -0.38170062, -0.87997669,  1.14984679]])"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X= preprocessing.StandardScaler().fit(X).transform(X)\n",
    "X[0:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import scoring methods\n",
    "from sklearn.metrics import jaccard_similarity_score\n",
    "from sklearn.metrics import f1_score\n",
    "from sklearn.metrics import log_loss\n",
    "from sklearn.model_selection import cross_val_score"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "button": false,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "source": [
    "# Classification "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "button": false,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "source": [
    "Now, it is your turn, use the training set to build an accurate model. Then use the test set to report the accuracy of the model\n",
    "You should use the following algorithm:\n",
    "- K Nearest Neighbor(KNN)\n",
    "- Decision Tree\n",
    "- Support Vector Machine\n",
    "- Logistic Regression\n",
    "\n",
    "\n",
    "\n",
    "__ Notice:__ \n",
    "- You can go above and change the pre-processing, feature selection, feature-extraction, and so on, to make a better model.\n",
    "- You should use either scikit-learn, Scipy or Numpy libraries for developing the classification algorithms.\n",
    "- You should include the code of the algorithm in the following cells."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# K Nearest Neighbor(KNN)\n",
    "Notice: You should find the best k to build the model with the best accuracy.  \n",
    "**warning:** You should not use the __loan_test.csv__ for finding the best k, however, you can split your train_loan.csv into train and test to find the best __k__."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "X_trainset, X_testset, y_trainset, y_testset = train_test_split( X, y, test_size=0.2, random_state=4)\n",
    "\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn import metrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.67142857 0.65714286 0.71428571 0.68571429 0.75714286 0.71428571\n",
      " 0.78571429 0.75714286 0.75714286]\n",
      "Best Accuracy is with neighbor  7\n",
      "Best Accuracy is  0.7857142857142857\n"
     ]
    }
   ],
   "source": [
    "Ks = 10\n",
    "mean_acc = np.zeros((Ks-1))\n",
    "std_acc = np.zeros((Ks-1))\n",
    "\n",
    "for n in range(1,Ks):\n",
    "    #Train Model and Predict  \n",
    "    neigh = KNeighborsClassifier(n_neighbors = n).fit(X_trainset,y_trainset)\n",
    "    knn_pred=neigh.predict(X_testset)\n",
    "    mean_acc[n-1] = metrics.accuracy_score(y_testset, knn_pred)\n",
    "    std_acc[n-1]=np.std(knn_pred==y_testset)/np.sqrt(knn_pred.shape[0])\n",
    "    #print(\"f1-score :: \",f1_score( y_testset, knn_pred, average='weighted'))\n",
    "\n",
    "print(mean_acc)\n",
    "knnbest = mean_acc.argmax()+1\n",
    "print(\"Best Accuracy is with neighbor \",knnbest)\n",
    "print(\"Best Accuracy is \",mean_acc.max())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "F1-SCORE::  0.7766540244416351\n",
      "JACCARD SIMILARITY SCORE::  0.7857142857142857\n"
     ]
    }
   ],
   "source": [
    "# F1 SCORE AND JACCARD SCORE FOR KNN WITH 7 NEIGBOURS\n",
    "from sklearn.metrics import f1_score\n",
    "from sklearn.metrics import jaccard_similarity_score\n",
    "neigh = KNeighborsClassifier(n_neighbors = 7).fit(X_trainset,y_trainset)\n",
    "knn_pred=neigh.predict(X_testset)\n",
    "print(\"F1-SCORE:: \",f1_score( y_testset, knn_pred, average='weighted'))\n",
    "print(\"JACCARD SIMILARITY SCORE:: \",jaccard_similarity_score(y_testset, knn_pred))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Decision Tree"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Solving environment: done\n",
      "\n",
      "## Package Plan ##\n",
      "\n",
      "  environment location: /opt/conda/envs/Python36\n",
      "\n",
      "  added / updated specs: \n",
      "    - pydotplus\n",
      "\n",
      "\n",
      "The following packages will be downloaded:\n",
      "\n",
      "    package                    |            build\n",
      "    ---------------------------|-----------------\n",
      "    pydotplus-2.0.2            |           py36_1          42 KB  anaconda\n",
      "\n",
      "The following NEW packages will be INSTALLED:\n",
      "\n",
      "    pydotplus: 2.0.2-py36_1 anaconda\n",
      "\n",
      "\n",
      "Downloading and Extracting Packages\n",
      "pydotplus-2.0.2      | 42 KB     | ##################################### | 100% \n",
      "Preparing transaction: done\n",
      "Verifying transaction: done\n",
      "Executing transaction: done\n"
     ]
    }
   ],
   "source": [
    "!conda install -c anaconda pydotplus -y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import \n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.model_selection import train_test_split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_trainset, X_testset, y_trainset, y_testset = train_test_split(X, y, test_size=0.3, random_state=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "X-trainset-shape::  (242, 8)\n",
      "Y-trainset-shape::  (242,)\n"
     ]
    }
   ],
   "source": [
    "# Print the shape of X_trainset and y_trainset. Ensure that the dimensions match\n",
    "print(\"X-trainset-shape:: \", X_trainset.shape)\n",
    "print(\"Y-trainset-shape:: \", y_trainset.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DecisionTreeClassifier(class_weight=None, criterion='entropy', max_depth=6,\n",
       "            max_features=None, max_leaf_nodes=None,\n",
       "            min_impurity_decrease=0.0, min_impurity_split=None,\n",
       "            min_samples_leaf=1, min_samples_split=2,\n",
       "            min_weight_fraction_leaf=0.0, presort=False, random_state=None,\n",
       "            splitter='best')"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "loanTree = DecisionTreeClassifier(criterion=\"entropy\",max_depth=6)\n",
    "loanTree # SHOWS DEFAULT PARAMS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DecisionTreeClassifier(class_weight=None, criterion='entropy', max_depth=6,\n",
       "            max_features=None, max_leaf_nodes=None,\n",
       "            min_impurity_decrease=0.0, min_impurity_split=None,\n",
       "            min_samples_leaf=1, min_samples_split=2,\n",
       "            min_weight_fraction_leaf=0.0, presort=False, random_state=None,\n",
       "            splitter='best')"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# train the model on training set \n",
    "loanTree.fit(X_trainset,y_trainset)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "#prediction\n",
    "predTree = loanTree.predict(X_testset)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DecisionTrees's Accuracy:  0.7019230769230769\n"
     ]
    }
   ],
   "source": [
    "#Evaluation\n",
    "from sklearn import metrics\n",
    "import matplotlib.pyplot as plt\n",
    "print(\"DecisionTrees's Accuracy: \", metrics.accuracy_score(y_testset, predTree))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.7019230769230769"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Jaccard Score\n",
    "from sklearn.metrics import jaccard_similarity_score\n",
    "jaccard_similarity_score( y_testset, predTree)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.7000725689404935"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#F1 Score\n",
    "from sklearn.metrics import f1_score\n",
    "f1_score( y_testset, predTree, average='weighted')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.externals.six import StringIO\n",
    "import pydotplus\n",
    "import matplotlib.image as mpimg\n",
    "from sklearn import tree\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f09a787c6a0>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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ixQGoef7fAUhasyCY/8PnQa9FkwEo3ah95hclSVIumzFxbPrjDT+tBqB563YA3PKPf2Y4p/ft9wOwZP4sACZ8PgKAiWOC+3qX8y/Nca5JY0ZF7N/1RD8A2nY+O+J4sYQSAFxz18MALFs4N8jy5UgAZk4Znz72pHadc5Tp65FDANidtBOArj2vylE9SZIkSZIkSZIkSZIkSZIkSZIkSVLeiMnvAJIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkFSRx+R1AkiRJkiRJkv4UwmEANkz8EID1EwYCkLRmUXA65SAARSvVAaBShysAqNL56kM1QqEMS2+b+w0A817oBUCdyx4DoGTdFgCsGPI0ADtXzAIgJr4wAGVO6AJA3dTxcQmlD6u9emQ/AFYNfS7ieNr+b4+naf/Wz5lmK16zSTB/2PPpc3atnAtA0cp1ATjx0c8jaqbs3wvA2s9eAWDT1BEA7N20GoBQ6nWVqNUcgGpdbwEgsUnHDDP+2pFyJlRrmJrzn0HG1fMBiC2cAEDZE88EoNZFDwAQX6LsYbV3LJ0BwOynugNQ5bRrAKh7xVNHzQWwadr/AFg04CYAal/yMADVzro5qvkFyfbF30XsV2jbI6p5FU6+EIDNM0an1pmSejy6+X9WodjIP8aJL1HuiGP379gcsV+8RuOoeqSN2/JD8Hn9ZdFkAEo3ah91TkmBcOpa4bMh7wIwavBbACxfHNx7kg8Ga4XqtY8DoNvl1wJwfu8bAQgdYZ0AMG38lwDce9V5ANz2SHD/bXRiawBee/YfACyeE9yzChUO7qknn9YVgFsfDsaXLJ14WO33/t+zALzR97GI42n7vz2eZtzKPZlmO65xcD9/s+/jAPw4f1b63Op1gufg9ZGTI2ru2xvU/ODVFwAYO3IIAOvWrAyuq1BwXQ2aBWuky266G4BWp3bJMOOvHSlnnQaNI65z6YI5ABQtFqwVTjkjuP9ff29wHaXLRH4Xz/9havrjW3t0BOCCK4N7/h2Pv3jUXADffPoJAI/dFqwfb37wGQAuueHOqOYXFHOmTTzs2OnnXxrV3C4XXA7AhM+D9eXsqd8Gx6Ocn5ltmzdE7Ndr1DyqeWnjJn45EoBZ301IP3dSu845yvTpB28CEBcXD0CXCy7LUT1JkiRJkiRJkiRJkiRJkiRJkiRJUt6Iye8AkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiQVJHH5HUCSJEmSJEmS/tDCYQAW/+d2ADZOGZrp8KQ1CwFY9v5DqfsL0s8dd/XzUbXctWIWACuHPAVAysH9EedT9u8JskwaAsC+zWsAaHZ/5tlyw46l0wFY8eETAIRTDh4+KJwSuXvwAABz/3VJUGPJ9xkXT73OXxZODLaLJgFQr/czAFTudGU2cj6eGik54nzK/r0ArJ8wKDXTNABOePQzAGILJ6SPLVnvJABK1D4BgA2pz3utix88bGxG1o19J3VcMQAqndor6us4monXVQcOv77cUKhkeQDa9J+dazX3blwZsV+s2vFRzUuo3jDTOn96qZ+Z/b9sBGD9xMEA/LLgWwASm3YCoEj5GkcsEV+8TMT+rtXzAShctlqmrdPGpdm7YUW0qSWlCqeuFZ6+61oAxgwfnOn4ZYvmAtD/kbuC/YXB/t+feSXqnotmB/e51579BwAH9u+LOL93z24AvvhkIADr16wKen40Juoe2TVvxhQABjz9AADJBw9fK4RTItcKBw4Ea4A+V5wT1Jg+JcPaadf5w+RxAMycMh6Au57sD8C5va7Pcs5/P3U/ACnJkffSfXuD9daowW8BMPf7yQC89r9gnVI0oTgAjVu0SZ9zfPNgzZD2vN9w3xMRY49k+HuvAVCkWLCmOOfSa6K+jqPpXDfo/dvryw2J5SoAMGz6qlypt3blssOO1W7QOKq5dY9vErH/Uwa1sqtUmXIR+0sXBGujilWPfF/+9bg0a1cuzXGWFYuD+/bCWcF6uv2Z5wJQ+jcZo7F62WIALu8QPMcbfwr+naJUmbIANG/dDoDLbv47AMc1bp7d2JIkSZIkSZIkSZIkSZIkSZIkSZJ0zIrJ7wCSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJBUkcfkdQJIkSZIkSZL+yDZO+SR1OxSAhGoNAah98UMAlKjbAoBQXCEAdq2cA8Cygf8AYP34gem1Kra7FICS9U7KvOd3wwCo3OlKAKqedRMAhUtXCnqsmgvAotduAWD74u8ASFqzIMhYvVF6rRrd7wSg9PF/AWD20+cDULPHvRHno7X5+5HBtbQPrqV619vSzxWpUBOAUExsxJyfv34TgB1Lvg+uo2xVAOr1fhqAUvXbAnBwz04ANnz7AQCrRrwIwPIPHgWgbIuz0msWKlUhupztLglydr8jYl7ac7jsvQcBSFq7EIC1o14BDj0/v1aly3UALH79dgA2Tv4YgMqdrsoww+6ffwRg++IpEePiipXMNHtBlpz6GqeJSygd1by4hMSI/YO7d+Rapvywe91SAGY8eGqG52PiCwNQufPVANTu+dBRayY27QjA1tljgEPv7bTPY6njTwYgec8uANaNew+ALTO/iKhzcPf2qK5B0iFjhgX3rTHDBwNQ5/gmANx4/5MANDyhNQCFCgVrhcXzZgLw0qN9APj0g+A+efbFV6bXbNyiTaY9vxrxIQDn9roegEuuD+5z5SpVAWDJvFkAPPG34N4ze9pEAJYtDNYpdRs2S6/V+/b7ATihbfCddPvFpwFwXZ9HI85Ha9yoYM3UtWfQ+7Kbg+usWqNO+piY2Mi1wrB3XgVg3vTgnlmxSnUA7nyiHwDN2rQDIGln8P0/+sN3AHj3pWAt8fLjwX273RnnAlCmfMWoc551UW8Aet92HwBlKwTrrR9Tn8N+jwRrpeWL5gEw6NW+wKHn59cuvPpWAJ6661oAvhw2CIDzrrghwwwrlwTrj9lTv40YV7xkqaPmL4h279p52LGSpRMzGHm4EqXLROwn7cy9+1nrDl0AmPL1aAD6PXIXALGxwV+3aN6mfdAzNf/IQf8FYNKYTyPq7Nqe80yfDn4rYj/tc5YdO7Ztjdim2bJxPQBjPw3WuhM+HwHAIy8Ha4dTzzov2z0lSZIkSZIkSZIkSZIkSZIkSZIk6VgTk98BJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEkqSOLyO4AkSZIkSZIk/ZFtmPghAKGYWACa9BkEQKHSFTMcX6pBWwCOv+nfAMx4qGP6uS0zPwegZL2TMu2Z2KQDAPWufDbD8yWPawVAtbNvAWDZ+w8BkLR6PgAJ1RtlWj8nStQNste/pm9wIBQ66pxN338asd/w5lcjaqWJLVoCgBrn9QFg3y8bAFg/7n0Ats78Mn1spY5XZJ6zzolBzmtfyDBnqfptAGj0tzcBmP7AqQBsnh5krdnj3sNqlm91LgArPnwCgHVfvwNA5U5XZZhh3dh3IvarnH5tppmzo90ba3K9Zl4Kh8PZnZmrOf7oUg7sA2DnsukAJK1ZCEDJei2POKdSh14AbJw0JJi7YhYA8/tdmWmvCqdcHDGPkL8zUsqqz4a8C0BMbLBWeP7dkQCUrVApw/HNW7cD4OGX3gbg6i4tAJg0ZmT6mMYt2mTas1X70wG4+6mXMjzfpOXJAFx6090A9H/kLgCWLpgLQN2GzTKtnxONTmwNwD3/HABAKIq1wrhRn0TsP/rK+xG10iQULwnA1XcGa58tG9cBMHLQGwBMGhPcx7tfft1RezZsHnyn3vf8axnmbNb6FACefP0jAK7s3ByA8aOHAXBdn0cPq9mx24UADHj6AQCGv/c6AOddcUOGGUaknk/T4+qbj5o7q8Yu25XrNfNK9tcJOZt7NN0uvQaALz4J3peLZs8A4P5re2Q678wLe6XOGwhAKCb799j9+/YCMGZY8O8iad8vbTqemeVaJ53SCTh0XQ2aBWvyIsWKAbB66Y8AfPBasN5Pe88/f99NALRs3xmAYgklstxbkiRJkiRJkiRJkiRJkiRJkiRJko41/t/bkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiTlorj8DiBJkiRJkiRJf2RJPy0GIJySDMC0Pi0jzofD4bRH/ObEYbX2bfkpqp6ljv9LVOOKlq8ZsX9w766o5uVEYqP2wYNQKOo5ezesACC+eCIAJeqeFNW8ss27ALB+3PsA7Nm4MuqeiY07BA+OkrNI6nNYtFKdoMf65UccG4qLB6Byp94ArBreF4Dti78DoFSDtgAk70sCYMPkj4MsTYIsxaocF3X+giquWMmI/YNJv0Q177fjflvnz6ZY5XoAtH/rZ+DQ98uBHZsB2DrnawCWD34MgLnP9wTgpCfHpdcoUr5GRM2YuEIANL0veN+tGdkPgE3TRgKwb1vQq3BiZQCqnnkjAIVKlQdg46QhAMSXKJvDq5OOPSt/XABASnLwWb745HqRA1LXBOHfrA1+u7/hpzVR9zzh5FOjGlelRu2I/d1JO6PukV0ntesMQCgLa4WfVi0DoGRiGQAandg6qnkndz4bgJGD3oioE42Wp54eVc6057BaneA+vnb5kiOOjY8PvovP7XU9AG/3exKA2dMmAtC8dTsA9iQFa7Yvhw4CoFX7IEvNesdHnb8gSihx+P19xy/bopq7a3vkuIQSpXIlE0B8ocIA9PvgCwDe/X/PAjBu1CcAbFoXrPHLVaoCQM/r7wCgTLmKAHzxyUAASpctl+0M4z8bDhx6Pi676W4AYmJjs1zrqf8MyfT88c2Dtfr/vRLkvvvy4HM2c8r4YDs52J7SpVuWe0uSJEmSJEmSJEmSJEmSJEmSJEnSsSYmvwNIkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJklSQxGV3YigUqg68C1QCUoDXw+Fw/1AoVAb4EKgFrAR6hsPhbaFQKAT0B7oCu4Grw+HwDzmLL0mSJEmSJEl5LCUlYjeckpztUuHkA1GNi4kvEl3BUCjbWbIrrnhiDmb//nnzQqVOVwKw+tOXAFg39m0ASjVoC8DGyR8DkLxnJwBVuvw1z7JMvK46kLP35ZEUKlkegDb9Z+dazSIVakXs7167CICS9VpmOi9pzcJM6/zZhWJiAShUuiIAlU69HICUA/sAWPb+QwBs/v7T9DnVut6SYa3YwsUAqHXRgxHbI1ny9j0R+8VrNctSdkmQEo5cK6QkZ+87+cCB/VGPLVykaFTjQr9dK4TDWYmULaUSy2Z77mF5/6TOu+J6AAa+8hwAI959DYDmrdsB8OWwQQAk7doBwIXX3ppnWTrXLQ5k/32ZmcRyFQAYNn1VrtSrVqvuYcdWLJ4PQJOT2mY6d9mieRH7VTOolVNFiiUAcMN9T0Rsj+RfD0S+rvWbnJjt3qMGvxWx37XnVdmuFa20z2PTVn8BYOaU8QBs3bQhz3tLkiRJkiRJkiRJkiRJkiRJkiRJUkERk4O5B4E+4XC4IdAWuDUUCjUC7ge+DofDxwFfp+4DnA0cl/rPDcCAHPSWJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJOkPKS67E8Ph8DpgXerjnaFQaCFQFTgP6Jg67B1gHHBf6vF3w+FwGPguFAqVDoVClVPrSJIkSZIkSdIfUtHK9QBIXjUXgDb9ZgIQV7RkvmXKllDk74ELJyf/bq2LVKwNwM5lM4Lt8uA5LFHnxEznbZ3zdcR+0Qq1ou65bf54AGpecE9wIBTKcNzeTasA2LN+eWqPmketXahkeQDKtz4PgE1TRwCwf/tGANaNfTeolXrdZZp2jjp3QVeqQVsA1o5+BYCN3w0FoFLHKzKdt3HKJxnWKehSDuyL2D+4d2eu1d6zcSVw6LkNxcQCUO6krrnWQzpW1KjbAIAle2YB8Mm04J6SUKJUvmXKjlBM5FohOfng79a7as26ACyYOQ2AhbOnA9CwectM5333zRcZ1onG9AlfAXDt3Y8AEDrCWuHn1SsAWLt8CQBVatY5au3EchUA6NT9IgDG/m8IAFs3bQBgxPv/AaBa7WCd2abjmVHnLsiatW6X/njQgL4AfDV8MADdL78u07ljhg2K2G/+q1q/t59WLgNgzLAPAIiJDe6xp559fpZrrV2xFIDZU78FoMlJwRqoep36Oc55NMFf7YC530+OOF6mfMU87y1JkiRJkiRJkiRJkiRJkiRJkiRJBUXM0YccXSgUqgWcCEwFKqb9MN/UbYXUYVWBNb+atjb1mCRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJBUZcTguEQqHiwCfAneFweEcoFDri0AyOhTOodwNwA0CNGjVyGk+SJEmSJEmScqTSqZcB8OMb0wCY+9wlANQ8/24AStRpAUBc0ZIA7N++AYCktYsA2PDt4PRalTtfDUDpRu3yOPXh4hJKR+zv+HEqAAd2bQMgvnhinvUu36obADuXzQBg0YCbAKjb+2kASh3XGoCDe3cBh56zdePeByAmrhAAZU48I+qeO5fPBODHN4PXqXr3OwAoVCr4XXVJq+cBsPS9BwAIJx8AoFzLblH3qNrlrwBsnPxxRK+ktQsBqNvryWDgkf+7eY61e2PN0Qf9gSQ2OhWAwmWD3wu4ffF3ACwf/BgA1bvdDkAoNvjji5+/ehOAzTNGAxBfvAwAZVuc9Tslzh1rPn0JgIN7dgCH3mdFytcEILZwMQD2/xJ8f2ydNQaAVcOej6hTqn6bo/Za8NI1AFTqcDkAJeq2BCAmLh6AX+Z/C8CyDx4BIGX/XgCqnBbMK1ymShauTBLAOZdcDcCz398AwN29ugJw9R0PAdDwxOA+l1AiWCts3bgegBWL5wMw+qN3ADi/943pNVuc0imPUx+uZOnItcCcaZMA2LFta3A+sUye9e54zoUALJgZrLceu/UKAO58oh8ATVv9BYDdO3cC8NmQdwH49IM3AIgvVBiAU7pEfx9fOHs6AM/dG6xLrrj1XgDKVqgEwJL5swHo9/CdABw8GKwVOnS9IOoeF11zGwBfDh0EwD/vCV7j5YuCdcjf/q8vAJn8GXuOjV22K89q57aT2nVOf1yxSnUAZk+bCMC/n7wPgF63BK9TXHywVhj69gAAJnw+AoBSZcoC0O6M7rme76HrewLQ7dKrAWjcom2QpVBwj50x8RsAXn7s7wDs27sHgAuuDN5jFSpXy3LPUR++BUA4HPzVirMvvjI70QEYNCB4v23fugmAjt0uAqBqjToAxBcK1tyrl/0IwAevBeNnThkPQEKJUgCccPKp2c4gSZIkSZIkSZIkSZIkSZIkSZIkSceamJxMDoVC8QQ/9HdgOBwemnp4QygUqpx6vjKwMfX4WqD6r6ZXA37+bc1wOPx6OBxuGQ6HW5YvXz4n8SRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJ+t3FZXdiKBQKAW8AC8Ph8Au/OvU/4Crg2dTtiF8dvy0UCg0G2gDbw+Hwuuz2lyRJkiRJkqTfQ8VTegKwffF3AGyY+CEA8/tdleValTr0yr1gWVS0Ym0ACiVWAuCXhRMB+O72xhmOb//WYb+3LduqnHYtAJunjwJgx9LpAMx/sXdU8+tc/jgAhUpViLpnuZbdANg4+WPg0Ot2JMUq1wOg2jm3Rt2jeK1mAJSs1xKAbXPGAhBbtAQAFdv1jLrWsSIUFw/AcVc9B8D8flcC8NMXr0VsD58YAqBu76cBiC2ckGmfSdfXSn8cTkkGoN0bazKds/j12wDYOGVopuPmvXDkz3HDW18HDr3/0hxM+gWAtZ+/GmxH/zvTHr9V4eQeACQ26XjUsTuX/QDAlplfRFW7dKN2ANTu+XCWMkk65MwLrwBg1nffAvD5x+8B8MB1F2apTrfLrs3dYFlUrVZwLyxXqQoAP0weB8C5J1bNcPy4lXtyrfcFV90EwITPhgEwb0aw7rr/mguimn/no88DUKZ8xah7duga1P5i6EAAPhvybqbja9RtAMDlN/WJukf9picC0OSktgBMHRd8NycULwnAWRdHtxY6VsTHF0p/3OeZlwG4/9rgHvjRf1+K2P5WKHWtcOfj/QEomlA8015d6pcGIDn5YPqxsct2ZTpnwcypAEwaMzLTcWlanNIJgJsefDqq8b+WfDDI9fnH7wNQpFiw9unU/aIs10qza8c2AD78T/+I7dHExgV/reTvz7wCHHr/SpIkSZIkSZIkSZIkSZIkSZIkSZKOLts/+Bc4BegNzA2FQrNSjz1I8AN/PwqFQtcBq4GLU8+NBroCS4HdwDU56C1JkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJ0h9Stn/wbzgcngiEjnD6tAzGh4Fbs9tPkiRJkiRJkvJFKPjPoPWvexGAxKadAFg/fiAAu1bNASB5324ACidWASChekMAKp7SM71U6cbtf4fAGQvFxALQ6Nb/ALD8wycASFo9DziUP096x8UD0PSejwBYM/oVADZNHQ7A3s2rAYiJKwxAidrNAah29i3Aoec8K0oe1wqASh2vAGDV0H8CkLR2IQCxhYoBULbFmQDUuujB4HjhhCz3qtzpSgB2LJ0e9Gx/aVCrSPEs1zpWpL2mze7/BIBVw/8FwM7lqb9nMJwCQPGaTQGo3v3OYF6TDr9nzFxT/dwgf5HyNQDYNG0kALvXLQHgYNJ2AOITSgOQUCu47op/CX63YvnW50bdq9Gd7wCwdtTLAGxfMg2AlNTPeNHK9YLa7S4BoHKn3gCEYnLyuyKlY1soda1w/79eB6BNx+De8ungNwH4ce4PAOzdHXwOy1euCkCd45sAcNZFwefwpFM6/06JMxYTG6wVHh/wAQADnn4AgCXzZwOwd3dSnvWOjy8EQN+BowH44NW+AHz9vyEArF+zMhhXKFgrNGjWAoDLbrobgNYdzshyz6Yt/wJA98uuA+CNf/0fAMsXzwegSLFgrdCuS3cArr8vWDsVTcj6/f3cXtcDMG/GdwCc3TNYOxRLKJHlWseKtNe0/+AvAXir35MALJoVrLdSUtcK9ZucAEDv2+8HoFX70/Ms0zNvDAVg0IDnAZj7/WQA9uwJPts16tYH4OzUz3Ta6x4bl/V77KSvRgGwbfNGAM66MFjT5uQ90+vWewEoX7kaAN98+jEAq5YuAiBpxw4AylaoBECzNu0A6PnXOwA4rnHzbPeWJEmSJEmSJEmSJEmSJEmSJEmSpGNVTH4HkCRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiSpIAmFw+H8znBELVu2DE+fPj2/Y0iSJEmSJEn6g/noo48AuOSSSwBo/9bP+RlHfwDb5n4DwLwXegFQ57LHAKh6xvV53nv5B48C8NOY/wLQ6tlJABSpUCvPe0t/ZgtfuQGAjrWKADBkyJD8jKMC5rdrhXEr9+RnHP0BTBv/JQD3XnUeALc98jwAF117W573fvnxewD45K1XABg4bh4AVWrWyfPe0p/Zo7dcDkD5YrGAawVJkiRJkiRJkiRJkiRJkiRJkiRJfwyhUGhGOBxuGc3YmLwOI0mSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEnSscQf/CtJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJUi6Ky+8AkiRJkiRJkiT9mYRTkgH4ZcG3AKwb+w4Apeq3BaBIhVr5kkuSJP0xpCQHa4UZk8YCMOL9/wDQrHU7AKrUrJM/wSRJkiRJkiRJkiRJkiRJkiRJkiRJ0u8qJr8DSJIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZJUkMTldwBJkiRJkiRJkv4MVg3vC8DqEX0zPF+9662/ZxxJkvQH83a/J1O3T2V4/vKb+/yecSRJkiRJkiRJkiRJkiRJkiRJkiRJUj6Lye8AkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiQVJHH5HUCSJEmSJEmSpD+jQqUrAlDt7JsBSGzWOT/jSJKkP5hyFSsDcMkNdwHQpuOZ+RlHkiRJkiRJkiRJkiRJkiRJkiRJkiT9zmLyO4AkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSQVJXH4HkCRJkiRJkiQppxKbdgKg/Vs/51mPmuf3idhKkqQ/j9YdzgBg3Mo9edbj6jv/EbGVJEmSJEmSJEmSJEmSJEmSJEmSJEnHtpj8DiBJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJUkHiD/6VJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJCkX+YN/JUmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEnKRXH5HUCSJEmSJEmSpPy2a+VsAGY+djYANc7rk36u5vl9MpyjP659W9amP94yawwAW2d9CcAviyYDED54AIAmdw8EILFpp2z12rFkWvrjVcP7ArBzxazgQEoKAMVrNQWgerc7gl5NOmRaM3nf7iD7D58DsGnaCACS1ixMH7N/+wYA4ouXAaBU/TYAVOt6W9CzZpPsXI4k6QgWz/kBgBvPPQWAq+98KHX7j3zLpOzb8NNqACZ/NSr92OSvRgMw67sJABw4sB+A594J7sOtO5yR6zme6fNXAL74ZGDE8c/mbwKgaELxqOrM/T5Y37zd/ykAFs2ann4uJRysR+o3PgGAK26/D4BW7U/PbmxJkiRJkiRJkiRJkiRJkiRJkiRJUpRi8juAJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEkFSVx+B5AkSZIkSZIkScpNsx4/BJ66LQAAIABJREFUJ/3x/h2b8qTHtnnjAJj/Yu/0Y+GU5AzHbl/8XbD9cSoADW9+FYByrbpnOH7NqP8XbEf2P2qO/b9sAGDTtP8BsHnGZwA0vuNtABKbdjpqDUmSjjU3ndcegG2bN+ZL/x8mfQPAl0MHAVCkaDEA9u7ZnaU6308YA8B911wAQEpyxmsRgNnTJgIw58pJADz68vsAdDynR5Z6SpIkSZIkSZIkSZIkSZIkSZIkSZKiF5PfASRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJKkji8juAJEmSJEmSJElSbipcrnr643KtugFQ5oQuAGyePgqA9eMHZqt2+OABAJa8fW+wn5Kcfq7qmTcCUL3b7QCEYoI/hvn56zcBWDX0OQCWvvsAAInNOgMQWzghokdckeIAVDj5QgDKtzkXgGJVGqSPKVSqAgB71i8DYMVHTwCwbf6EoMd7DwLQ6rkp2bpOSZIKskrVagLQsWuP9GN/Ob0rAOM/Gw7Apx+8mas99+/bm/6470PBWuHMHr0AWLJgDgDLFs6JqtaBA/sB+NcDtwGQkhysR3r+9W8A9Lrl3vSxsXHBemTYOwMAeKPvYwC8+HAwtk3HMwAomlA8S9cjSZIkSZIkSZIkSZIkSZIkSZIkSTq6mPwOIEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJElSQRKX3wEkSZIkSZIkSZJy0wkPf3rEc1tnjclR7W0LJgCwb8taAEo1aJt+rs6lj2Y4p0b3OwFIWjUPgM0zRgOw5YcvAKhwco+I8dW63hp1noQajQFo9Le3AJh6dwsA9m5aBcCBXdsAiC+eGHVNSZIKugHDJxzx3OSvRudJz7f7PZX+ePfOHQDc8vBzANx12VlZqjVj4lgANvy0GoDmrdsF9f7xzyPO6X37/QAsmT8LgAmfjwBg4phg3dTl/EuzlEGSJEmSJEmSJEmSJEmSJEmSJEmSdHQx+R1AkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkqSCJC6/A0iSJEmSJElSQRJOSQZg3dh3ANgw8cP0c3s3rUodFGyKVKwFQIW2FwBQudOVAMQUKpph7e2LvwNg/bj3ANixfCYA+7b+BEBckRIAlKh7Uvqc6ufcBkDJ41plmnvb3G8AmPdCLwDqXPYYAAnVGwGwauizAOxavQCA+ITSQebTrjmsV5qfv3oz2H4dbPdtXgtA4XLVAajV414AyrXqnqVsEfmqNQzyDftnar75AMQWTgCg7IlnBr0ueiDIXaJspr2yJBy8kGmv8foJAwFIWrMoOJ1yEICileoAUKnDFQBU6Xx1MD8UOnLpI7yPcvoeUs6lfQ7TVGjbI+q5FU6+EIDNM0an1pqSejz6GkeS9poXLlMVgOQ9SQDEFi6W49qScldKcvAdP/y91wD4/OPgvv7z6hXpY1JvMVStFdxDTj/vUgDO7fVXAIoUzfizPXvaRABGDvwvAAtmfQ/App+De3CxEsFaodGJbdLn9Lr57wA0aXlyprmnjf8SgHuvOg+A2x55HoC6DZsC8N/nHwVg2cK5AJQonQjABVfeBMDlqX1+bejb/wZg2DuvArD+p9UAVKpWE4Dr+gQ1O56T+ffkkbIB1GnQGIA3+gZrh6UL5gBQtFiwVjjljGAdcv29jwNQuky5THtlRTj1hfxsyLsAjBr8FgDLFwfrleSDwVqheu3jAOh2+bUAnN/7RgBCR1grpL2H4Mjvo+y+h5T7li+aB8BH/+mffuzBfsH6uGTq5ySr5qR+1tOcfv6lUc/tcsHlAEz4fAQAs6d+GxzPQg1JkiRJkiRJkiRJkiRJkiRJkiRJUnRi8juAJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEkFSVx+B5AkSZIkSZKkgmTlx88AsPazfx917K6VcyK2obhCAFQ57ZqIcfu3bwRgzrM9Mq13YNdWALbOHpN+bNvcbwBoeu9HAJRq0PaouQB2LpsBwIoPnwAgnHIw4vy+/XsAWPnx0+nHYuILReRdOzrj52DP+mUALBxwMwAtKtYBIKFG46iyAexYOj013+Op+ZIjzqfs3wvA+gmDgvFLpgFwwqOfARBbOCHqXocJhwFY/J/bAdg4ZWimw5PWLARg2fsPpe4vAOC4q58/4pxo30fRvodyYuJ11YHDn+PcUKhkeQDa9J+d67Xzyt6NKyP2i1U7Puq5CdUbZlorJ9I+V0lrFwFQrsVZAMTEF861HpJyx+vPPQzA4NdePOrYH+fOjNjGx8cDcMFVN0eM27ppAwB39OySab3tW7cAMOXr0enHpo3/EoAXBgX3yOat2x01F8CCH6YCMODpBwBIPhi5Vti7ZzcAr/8zuN74Qoe+j7ZuWg/AB6++kGHtNct/BODx23sDUK12PQDqNWoWVbZ5M6akP/73U/cDkJIceR/btzdYy4wa/BYAc7+fDMBr/5sIQNGE4lH1ykg4da3w9F3XAjBm+OBMxy9bNBeA/o/cFewvDPb//swrGY5Pew/B0d9H0b6HcqJz3eC5+u1znBsSy1UAYNj0VbleO6+lpKQA8K8HbgWgVYdDn8/O3S7KUe21K5dF7Nf+/+zdZ5yU5dWA8Wt2l6UsbalLl6J0QUBAqWJARVAjKEVRIokaxahg7MGoMYk1do1GJSpFsb4iKqgRJIIIAgIiVXroTXrZeT88u4ODu8uWgcH1+n952n2fc56Ze+Y5gr+hfu776LoNmkQdrz4sliRJkiRJkiRJkiRJkiRJkiRJkiQpdhLiXYAkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSYVJUrwLkCRJkiRJkqTCZNPXHwCQWLQEACf97vHItbKN2gOQkFgEgN3rvgdg/RdvRs35iVAIgNTGHQGo2nUQACk1mwCQXLoCAAd2bgNg24IpkakLX7gRgJXjngSgTP22ubqPDdP+D4Bq3X4XtU0qWQ6ALXP+A8B3z14TmbPinUcACIfTATjxNw8DUP6UbsFtJCQGtYwNXpNVHz4bbMc/B0D93z6Wq9oANn71HgCV2/cBoEbP6wFILlMJgB3L5wCw5JXbAdi5an6Q6/2nAKh14c25znW49VPezNi+BUBK9YYA1L7oDgBK1W0BQCgpOahl2TdBLSPuBGDtxBEZtfcFoHS9lj/Jkd06yvcaUswc3P1D1HFSStlcz01KSY06PrBre8Hr2bsLOPRZTCpRCoDafe8qcGxJR8fk8cEzrFiJFABuf+QFAFq26xwZk5gUfM+vXrYYgPFvjwKgeErJLGOGMnqFVh3OBKDXwOA7oV6jZgCkVgyejz9s2wrA7KmfR+b+/Y9XAjDy6YcAaNa6fa7u49OxbwDQ+4rBAFw06DoAyqSWB2DaxAkA3HPdZQAMf/S+yNxwetAr/PH+ZwBo17UHAAkZvcKIp+4H4LXng95gzAvBc/C2h/+Vq9o+e/+tyP7ZvQcAMGDwLQCUr5QGwMK5swB4dNgNACz9bi4AI58N+pdBQ/P/PToh4/2a8M5oAOo0CHq2q279CwANm7cGIDk56BUWzJ0JwON3DQVg7KgXATjnouC1a9yiTVT8zDUE2a+jvK4hxd67r/wTgGULgz703x/PjFnsXTui+5HSZVOzGflTpcqWizre+cO2mNQkSZIkSZIkSZIkSZIkSZIkSZIkSfqphHgXIEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJElSYZIU7wIkSZIkSZIkqTApWq5q1HH5U7pF9kMJ0X8km1KjEQC1+zTKMWZy6YoAnND7dgBWjnsKgO3DbwZg//ZNAITTD2QbY9fK+Ues/cdSm54BQJ1+d2d5vUKrc4Ho+9s4/f1gTt+7AEjr2C/LuSdcdAcAayeODGpbvTBPtQGUqnMKACdd8UhwIhSKul7mpDYANPrDiwBMv61jRo1jAah14c15zplp3eTXgpQJiQA0GRrcR3LZylmOL1O/LQANrn4agBl3dAZg08wPAShdr+VP5mS3jvK7hgqi/Qsrj1rsn6NwOFyQ2TGr4+DeXQB8+/hAAHb9bzEATYaMAKBYhRoxyyUptiqmVYs6bver4JmamPTTv7qt2/BkAH6fsc1OaoVKAFx5870AjHz2IQAevn0wAFs2bQDg4IHse4WlC+YesfYfa90peDYNHvZgltc7nnMBAKd3De5v0gfvRK5dc+f9AJzbZ2CWc6+69T4Axo4eDsCyRXnrYxo2axXZv+XBfwIQOqxXOLl1OwD+8tzrAFzWpRkAE8e9DcCgoXflKeePfTDmZQASEoNe4cGX3wOgfKW0LMc3a90egD89PhyAgV1bAPDfCcG8xi3aRI0/fA1B9usot2uoID5dsuOoxf452rh2DQD/evDPAFx5a/C5rFjlp+9bfhWkHylYLyNJkiRJkiRJkiRJkiRJkiRJkiRJyouEeBcgSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSVJh4g//SpIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIUQ0nxLkCSJEmSJEmSCpM6/e4G4NsnfwvAVzefHrmW2rQzACVrNAKgVN1WwXGtJjnG3L54OgDf3N8LgPCB/XmuK33/njyNL1P/tFyNK1q+ehZz2+Y4J5SQCEByahoA+7dvyFNtAKmNO2UEC+U4rljFWgAUT6sDwO61S/Oc63A7Vy8AIJx+EIBpQ1tFXQ+Hw5l7HHYh6nDvptXZ5shuHeV3DSl2kkqUjjo+sHNrrucePvbwWEeevy2yP+/RSwHYuXI+AE2GvAoc+fMnKf4GD3sAgD9d3Q+A/p0aA9C6U9fImLoNmwLQuEXwmT6xcbMcY86dMRWAG/ueBcD+/fvyXNfePbvzNL552w65GpdWreZPzjVr3T7HOQmJQa9QMa0qAFs2rM9Tba06/iqyHzpCr1C1Zm0Aqtc5EYBVSxflKVdWli38FoD0g0GvcNFp9aIHZPQE4cN6g8OP161emWX8zDUE2a+jvK4hxc6jw24AoHaD4D05/9IrY54jpVR0D7F965Zcz92xLXpsSqkyMalJkiRJkiRJkiRJkiRJkiRJkiRJkvRTCfEuQJIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZKkwiQp3gVIkiRJkiRJUmGSUqMRAK3+NgmA7YumR65tXxzsb1v4JQDL330EgCIlywHQ4PfPBDGqN4yKufL9JwAIH9gPQM3zhwJQ+fReACSnVgEgISk5mBAKReZOv60DAAd2bM7TfSQUKZqrcaEf5Yqcy+XczDrD4fRc13VcSI+uN5x+MF9hwgf3Z3stu3WU3zVUEJMH1Qjqzed95iS5dEUA2jw2O+axj5ZilU6IOt616rvIful6rXKcu3Pl/BxjZWff1nUAzH24f+Tcng0rAGg8ZAQAZU5qk6tYkuKvbsOTAXjlk+C7b+7XUwGYN2NqZMw30/4LwL8fvQ+AMuUqADDsiZcBqNOgSVTMkc88BMD+/fsAGHjDHQB0+3XwvVEhrSoARZKDZ/SPn98DujQDYNuWjXm6j+SixXI1LqteIblo3nqF9J9Zr3B4vekH8/cMzXw/D5e5hiD7dZTXNVQQXeqWBPJ/nzlJrVAJgLenL4957FjbvnULAJPHvxd1/ozaJfIc65zGFaOOP1n8AwCJScH/4lH9hLpR179fMA+AJi3bHjH2ku/mRh1XOyyWJEmSJEmSJEmSJEmSJEmSJEmSJCl2EuJdgCRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJhUlSvAuQJEmSJEmSpMIolBD88WuZ+m0j5368D5C+bzcA029tD8CiF4cC0HzYuKhxezasACC5dEUAal0wNMfce9Yvi+zvXvc9AEVSyuSp/uPdlnkTAaj16z8GJ0KhLMft2bAcgN1rlwJQvFKtAucuXqUeAAeXzwGgzaMzAUgqXrrAsQ93+DrK7xpS7GS+B6vGPQXA+qlvRa6ldb40x7nrp7yZZazsZH6W5zzUF4D9O7ZErjW5aRQApeu1ykXVko5HiUnBd3yz1u2jtj+2Z/cuAAZ0ORmAB265GoBn350cNW7NiuB5n1qhEgADb7gzx9xrli+N7K9ethiAkmXK5u0GjmPTJ30c2b9iyDAAQtn0Cpmv3aqliwCoWqtOgfPXrFsfgEW7ZwHw5rTg9U4pFft+7EjrKLdrSAUXTk8/ZrlOznifRz7zMAAfvzMagJ79Bx1x7oS3R0YdZ/XdI0mSJEmSJEmSJEmSJEmSJEmSJEmKjYR4FyBJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJUmGSFO8CJEmSJEmSJKkwmX1fTwAqnX4RAGXqt41cK1ahJgDpB/cBsPXbyQDs37klOL9/T5Yxi5avBsCuNQsBWPPJSxk5ekWN277oKwCWjrrr0Mlwej7v5Pj2w9KZACx8cQgANXpeD0BymUoA7FwxF4DFr9wGQPjgfgAqtOpR4NxpHfsFuV+YBsCcB/oAUOuCoJZSdVoAkFS8NAD7tq0Lalr1HQDrPh8NQJUuAwEo26j9T3Jkt47yu4YKov0LK2Me8+cstVFH4NDnctuCqZFrS0ffDUCNHtcBEEoM/hpmzccvArBxxjgAipQsB0D5FmdnmWPn6mCtzH2wL3DofW160+jImFJ1TinorUiKk2sv7AzAWb0uAeDk1sFzoEqNEyJjDuwPvudn/PczALZv2QzA3j27s4xZuWoNAJYvmg/A2/9+BoBuF/aPGjdn+hQAnrrn5si59PTC1yvMnz09sv/AzVcDcOm1wT2Xr5QGwKJ5swF49E83AHDgQNArdOr+6wLnP7fPQAD+/tWVAAy5pDsAA6+/A4CGp7QGIKVU0CtsXr8WgO8XzANg3Ov/BuCCAVcB0KLdGVHxM9cQZL+O8rqGCuLTJTtiHvPnqEy58gB8tizvr/Ggc9oAsGT+NwB8MG8DAMVTSmY5vmX7LsChz/7saUFP+PRfbgHgkmsOfcaTigT9yFvDg++FSR++G1Vv+24981yvJEmSJEmSJEmSJEmSJEmSJEmSJCl3EuJdgCRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJhUlSvAuQJEmSJEmSpMJkx7I5AGxfPCPPc9M6XZLl+SqdBwCw5ZtPAVjy6h1R28OVrNUksp9SrQEA+7aty3M9x7MKrXoAsP6LNwBYN/m1HMeXqFIPgOrnXlvg3JXbXQzAtgVTo3LPe/TyPMXJ7v2G/K+jnGL+kix4bnBkf/2Ut3IcO/eRrF+zhtc+Bxxaa5lCSUUAOPHyBwCY9+hlkWurP/pn1PYnQiEA6g74KwCJRVOyHLZm/PMA7Nu2Pur8rHvPzTpuDlrcPQGAlJqN8zxX0tGxcO4sAOZ9/WWe5/bod0WW58+7ZBAAX372EQCP3TUkanu4Exs3i+zXrh98P2xa/78813O86tT915H9j94aAcAHY17OcU7NuvUB6H/10ALnP6vXpQDMmvo5AB++8QoAtw3qlac42b3fmWsI8r6Osov5S3PfDb8BYMI7o4849ubLz8/y/N1PjwSi19uxUqRIMgBD//YkALdecSEAr//r8ahtVkIZ/cgN9zwGQPGUkketTkmSJEmSJEmSJEmSJEmSJEmSJEn6pUuIdwGSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJBUmSfEuQJIkSZIkSZIKk+bDxgGwduIIALbO/2/k2p6NKwBITC4BQPEqdQGo3L4vAGkd+mQZs/wpZwFQ/6qnAFg17kkAdq/7HoCkEmWCcc27AXBC79sjc+c8lHXMn7vSJ54KQFrnSwFY/tb9AOxcNR849BqXbxG8dpmvSWLRlIInD4UAOGnQPwBIbXoGcOg937H8GwAO7t0FQNHUqgCk1GgIQOV2FwNQtnGHbFNkt47yu4YUe5nv+8m3vhk5t/ydhwD4Yems4EQ4HYCStZoCUKPnDcHcJp2OVZmSjkPPvjsJgLGjXgJg5pSJAPxv5bLImGIlgu/5GnVOAuCciy6L2h6uXdeeANz52HAARj3zMACrli0GoGTpoFdo96seAPzulnsjc4de2r0Ad3N8atrq9Mh+z36DAHjhoT8DsHTBPODQa9w+47XLfE2Kp5QscP5QRq9w60PPAdCmc9CPjB39IgAL53wNwJ5dQa9QsUo1AOo0aALA2b0HANCyXZcs42euIch+HeV1DennqXWnoP9/bPR4AF569C8AfDdremRMekY/clKT5gAMuO5WAE7t8KtjVqckSZIkSZIkSZIkSZIkSZIkSZIk/VIlxLsASZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIKk1A4HI53Ddlq1apVePr06fEuQ5IkSZIkSdJx5vXXXwegT58+AHR4aU08y9FRtmXOfwCY+8glkXN1+t0NQLVuv4tLTZIKbv5TVwLQ+YRiAIwZMyae5aiQObxX+GzZ7niWo6Ns2sTxANx8+fkADB72YORa7ysGx6UmSQV31zX9AahYIhGwV5AkSZIkSZIkSZIkSZIkSZIkSZJ0fAiFQjPC4XCr3IxNONrFSJIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZL0S+IP/0qSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSFEP+8K8kSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSTHkD/9KkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkhRD/vCvJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEkx5A//SpIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIUQ/7wryRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJMZQU7wIkSZIkSZIkScpJatMzAOjw0po4VyJJko5HrTt1A+CzZbvjXIkkSZIkSZIkSZIkSZIkSZIkSZIkSdIhCfEuQJIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZKkwsQf/pUkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkKYb84V9JkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkmIoKd4FSJIkSZIkSZKOvh3LZgMw8+5zAKh5/lAAal0wNG41qeDWT3kTgAXPXZfl9WpdfwtAnf73RJ0/uHdXZH/T1x8CsGHauwDsXDkfgH3b1gFQpGQ5AMqc1AaA6t0HA1CyVpOC30CM7N20CoBNsyYAsHnW+Mi1rd99AUD4wH4AmgwZAUBq0zPylWv7omkALH/nYQB++H7WoYvp6QCUPKEpADV6XB/katIpNjky4ucnx67/LQZgxu0ds7xeqk4LAJr/aWyeapVUeCz45msArjqvHQADb7gjY3tn3GpSwU14exQA9914RZbXe18RPNcHD3swy+tnN6oQ2d+za2eecg+573EAzrvkd1lef+PFJwF48p4/5iluVq669T4A+l09pMCx8is94zk9/u2RAPzfq88DsGpZ8AxOP3gwMrZqrToAnHPRZQD07D8IgKSkIjnm+GbafwH46M1XAZgzfQoAa1ctB6BosWIAnNS0RWRO799cC8BpZ3bPMfaKJQsAuOzM5lleb9j8VACeeWdSjnEkSZIkSZIkSZIkSZIkSZIkSZIkSYckxLsASZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIKE3/4V5IkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZKkGEqKdwGSJEmSJEmSJOnYWvn+E4f233ssx7H7tq4DYMO0/wNg44wPAGh8/XAAUpuecRQqzJtZ95wLwL7tG45aji1zPwNg3j8GABBOP5jt2G0LpgbbhV8C0PD3zwJQ4dSecc8hSVJh1OL0zvEugb/eeAUAH7/72hHHLpwzM2o75ZOgv7p/+DsAhEKhqPGrly0B4A8X/yrHuPv27gFgxuRPI+cy96+5834ALv7tH45YnyRJkiRJkiRJkiRJkiRJkiRJkiQpNhLiXYAkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSYVJUrwLkCRJkiRJkiRJsdHg6mcAqNjm/BzHJRUrGdmvdFqvjDnnAVCian0AkstUAmD32iUAfP/6vQBsmTcJgMWv3A7AqQ9MiUntBVG0Qg0AKpzaA4ByzbtGrm2c/j4AayeOyFfs8IH9ACwafnNwnH4QgGpnXQVAjR7XRcaGEoK/dlnzyYsALH/rAQAWv3wbAKkndwEgsWhKvnJkxs9PjhJV6gHQ4aU1UeenXNMg+5uXJBU6w554GYAuPS/K89wmrU4D4Mk3Po1JLb2vGBy1zY09u3YCcOGptQGoXL0mAPVPbhGTmvJj0bzZAHz87msAFEkuCsDQvz0JQLtfBf1JQuKhf5d5xufBa3j/H4Nn/bSJ44Pzk4PzrTqcGZUjlBDMPbVj0OOc1esSABqc3BKASlWrA7B5wzoA3n31ucjcUc8+AsDzDwwD4Ny+AwFIKVk6KkfNukEP+Nmy3VHnz22alu29S5IkSZIkSZIkSZIkSZIkSZIkSZJylnDkIZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkKbeS4l2AJEmSJEmSJEk6tqp3vzbXY1NqNgag0R9eAuDLIS0A2LNhOQD7d2wBoEjJ1FiWmCfN/zQ222ubZ00oUOwt304CYO+mVQCUqd8WgDp978p2Ts2eNwCwc/lcADbOGAfApq8/AqDSaRce8xySJBUGn7w3BoBdO38AoPvFl8ezHACWLfw26viciy4D4Oxel2Y7p+M5FwCwdEHwHB/+6H1BrEXzAWjV4cyo8VVr1gbgwZf/L8da0qrXAuCqW++LnPt25lcAzP7ycwBWLF4AQMPmp+YYS5IkSZKT3DyYAAAgAElEQVQkSZIkSZIkSZIkSZIkSZJUcAnxLkCSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSpMIkKd4FSJIkSZIkSdLxbNuCKQB88/deAFTtOgiAuv3vzdX8jTPGRfbnP/lbAE7ofRsANc697rBcUwFY+9krAGxfOhOAvZtXA5BUrBQApeq2zJg/GIDSJ56a6/s5krWTRgKw6KWbAGh47XMAVGjVI89zG133IgDlW5yd9YRwGIB1k1/LmD8CgJ0rvwsupx8AoHhaHQDSOl0amVq1y8BgJxQ6Yl2KjYTk4gAULVcNgIO7dwKQWLRE3Go6FjI/l5kqtb0w13MrnRZ8b2R+D2R+n1Q6LTrGscgh6eiZ/eXnAFzfpxsAvX5zLQDX3fVQruZP+vBdAIZd3Tdy7nc33wPAJdf8MTrXtMkAvDfiXwB8O+srADasWQVAiVJBr9DolDbB/N8Hz+QmrU7L9f0cyfujXwLgwVuvAeDup4Pnf6fuv87VvB/P/ctzrwPQvlvPLOeEM3qFD8a8HBVj6YJ5ABw8EPQKNWqfCECP/lcAcMGAqyIxQvYKhcrYUUF/mZRUBICuv+4Xz3IAKFexcuxiVUqLWaxMSUWKRB2XLV8x5jkkSZIkSZIkSZIkSZIkSZIkSZIkSVlLiHcBkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiQVJknxLkCSJEmSJEmSjmdl6p8GQPG0OgCs/+JNAGpf/CcAEpKSc5y/btKoyH4oIRGAyu0ujhqzb9t6AL75+4U5xtq/YzMAm2dPAGDLnP8A0PTm1zNqbZvj/ONGOAzAguevA2D9lLdyHL5z5XwAlrx6x4/OfQvAiQMfjGlpkwfVCEpMPxjTuADJpSsC0Oax2TGPfSzsXrsEgJ2rvgOgQouzAUgoUjRuNR0Le9YvizouUb1Bruem1GiYY6xjmUPS0dOsTQcAatQ+EYAJb48E4Orb7gOgSHLO35PjXhsOQEJiYuTcWb0ujRqzecM6AK6/uGuOsbZt3gTAlE/GATBt4ngAHhn5QVBr6/Y5zj9ehDN6hb/eeAUAE94ZneP4Jd/NAeCxYTcGx/PnRK7d9LenYlpbl7olAUg/GPteIbVCJQDenr485rFjYcWSBQD079QYgPWrVwJQplx54ND66vf7mwA4sXGzmOX+fsE8AObP+gqADmedB0DZchViliO/TjmtEwAnnNQIgA/GvAxAoxatAWjftScAoYRQZM6Mzz8FYMy/ngCgctWgBz39zO75qiE9PR2AzevXRtUAMGNykKt1p24AVKlxQr5ySJIkSZIkSZIkSZIkSZIkSZIkSZLyLiHeBUiSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSVJgkxbsASZIkSZIkSfo5SOvQD4Dvx9wHwKavPwSgYuvzshy/b8taALbM/SxyLvXkLgAkl60cPTgUCq437ghA1a6DAEip2SQYX7oCAAd2bgNg24IpACx84UYAVo57EoAy9dvm+b7iYf2UNzO2bwGQUr0hALUvugOAUnVbABBKSgZgx7JvAFgy4s5IjLUTRwBQuX1fAErXa3m0y/7FOrh3FwDfPXsNAEklSgFQu+9dcavpWDq4+4eo46SUsrmem5SSGnV8YNf2uOWQdPSdc/HlADx3f/C8+nz8ewB06dE7y/Eb164BYNqkCQC0PePsyLUKlatEjQ1l9AqtOpwJQK+BwXdyvUbNAEitWAmAH7ZtBWD21M8B+PsfrwRg5NMPAdCsdft83NmxN+HtUcH2ndEA1GkQ9ERX3foXABo2bw1AcnLQKyyYOxOAx+8aCsDYUS9GYp1z0WUANG7R5miXXeht37I5aptp0/qg7/107BsATPrwXQCGPfkKAB3PPr/AuceOfinquHvG5+14kJCYCMA/Rn4AwNN/uQWAB/54FQB/T/9dtnPbd+sJwOBhDwJQrHiJXOVcsWQBAJed2TzL68lFi0X2LxgQ1JH5+ZEkSZIkSZIkSZIkSZIkSZIkSZIkHTsJ8S5AkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkqTCJCneBUiSJEmSJEnSz0Gl9hcDsOzN+wFYN2kkABVbn5fl+HWTXwMgnH4wci6tY/8sxyaXrgjACb1vB2DluKcA2D78ZgD2b9+UEetAlvN3rZyfy7s4PmS+NqGERACaDA1ey+SylbMcX6Z+WwAaXP105NyMOzoDsGnmhwCUrtcyJrW1f2FlTOIUBgf37gLg28cHArDrf4sBaDJkBADFKtSIS13HWjgcLsjs4yaHpKPvnIsGAPDCw38GYNxrwwHo0qN3luM/eOMVANIPBr3CuX0uzzZ2aoVKAFx5870AjHz2IQAevn0wAFs2bQDg4IGse4WlC+bm6h6OFx+MeRmAhMSgV3jw5fcAKF8pLcvxzVq3B+BPjw8HYGDXFpFr/50QzG3cok1Mavt0yY6YxPm5aNnujMh+j76/AaD+yUHfVaxECQBWLF4IwKh/PgzAxHFvA/DgLVcD0KpDFwBKpJTKc/59e/cAMOHtoF/MXANtOp+V51hH28K5MwFYNG82AOnp6Uecs/S74LP57ayvAEirXismtWS+bgDzvp4KwJKMXE1ato1JDkmSJEmSJEmSJEmSJEmSJEmSJEnSkSXEuwBJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkgqTpHgXIEmSJEmSJEk/B8mlKwJQrvmvANg08yMA9m5aBUDR8tWDgeEwAGsnvxbMK1MpEqNcszOzjL198XQAvrm/VxDiwP481Za+f0+exsfbztULAAinHwRg2tBWUdfDGa8hhDnswk9i7d20Oub1/dId2LkNgHmPXgrAzpXzAWgy5FUAytRvG5/C4iSpROmo4wM7t+Z67uFjD491LHNIOvpSKwTP/NO6nAPAfyeMBWDd6hUAVK5WEzj0nPtgzMsAlKtYGYC2Z5yTbey5M6YCcGPfswDYv39fnmrbu2d3nsbH27KF3wKQfjDoFS46rV70gIzXMHxYb3D4McC61SuPQoW/HPc9P+aIYxo0awnAn58aAcCQ/sFanjllYrD9Iti269ojz/knfvAOANu3bgGg39VDAEhITMxzrKNl/uygl7/tiguBQ5/1+4cHtTduEfROCYmH/l3mBd98DcATd98EwD2DBwCQUrIUAG06n5Vjzpp16wPw2bLgs535Wdm8cT0AX/7nw8jYp/9yKwBDL+kOwPA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\n",
      "text/plain": [
       "<Figure size 7200x14400 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Data Visualization\n",
    "\n",
    "dot_data = StringIO()\n",
    "filename = \"loantree.png\"\n",
    "featureNames = Feature.columns[:]\n",
    "targetNames = df[\"loan_status\"].unique().tolist()\n",
    "out=tree.export_graphviz(loanTree,feature_names=featureNames, out_file=dot_data, class_names= np.unique(y_trainset), filled=True,  special_characters=True,rotate=False)  \n",
    "graph = pydotplus.graph_from_dot_data(dot_data.getvalue())  \n",
    "graph.write_png(filename)\n",
    "img = mpimg.imread(filename)\n",
    "plt.figure(figsize=(100, 200))\n",
    "plt.imshow(img,interpolation='nearest')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Support Vector Machine"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The best accuracy is ::  0.7857142857142857\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/envs/Python36/lib/python3.6/site-packages/sklearn/svm/base.py:196: FutureWarning: The default value of gamma will change from 'auto' to 'scale' in version 0.22 to account better for unscaled features. Set gamma explicitly to 'auto' or 'scale' to avoid this warning.\n",
      "  \"avoid this warning.\", FutureWarning)\n",
      "/opt/conda/envs/Python36/lib/python3.6/site-packages/sklearn/svm/base.py:196: FutureWarning: The default value of gamma will change from 'auto' to 'scale' in version 0.22 to account better for unscaled features. Set gamma explicitly to 'auto' or 'scale' to avoid this warning.\n",
      "  \"avoid this warning.\", FutureWarning)\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "X_trainset, X_testset, y_trainset, y_testset = train_test_split( X, y, test_size=0.2, random_state=4)\n",
    "\n",
    "from sklearn import svm\n",
    "\n",
    "knls = ['linear', 'rbf', 'sigmoid']\n",
    "mean_accuracy = np.zeros((len(knls)))\n",
    "for kernel in knls:\n",
    "    clf = svm.SVC(kernel=kernel)\n",
    "    clf.fit(X_trainset, y_trainset)\n",
    "    svm_predict = clf.predict(X_testset)\n",
    "    mean_accuracy[knls.index(kernel)] = metrics.accuracy_score(y_testset, svm_predict)\n",
    "\n",
    "print( \"The best accuracy is :: \", mean_accuracy.max())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/envs/Python36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1143: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no predicted samples.\n",
      "  'precision', 'predicted', average, warn_for)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0.6914285714285714"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# SVM\n",
    "##for Linear\n",
    "from sklearn.model_selection import train_test_split\n",
    "X_trainset, X_testset, y_trainset, y_testset = train_test_split( X, y, test_size=0.2, random_state=4)\n",
    "\n",
    "from sklearn import svm\n",
    "clf = svm.SVC(kernel='linear')\n",
    "clf.fit(X_trainset, y_trainset) \n",
    "\n",
    "svm_pred = clf.predict(X_testset)\n",
    "svm_pred [0:5]\n",
    "\n",
    "from sklearn.metrics import jaccard_similarity_score\n",
    "jaccard_similarity_score(y_testset, svm_pred)\n",
    "f1_score( y_testset, svm_pred, average='weighted')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/envs/Python36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1143: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no predicted samples.\n",
      "  'precision', 'predicted', average, warn_for)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0.6914285714285714"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.metrics import f1_score\n",
    "f1_score( y_testset, svm_pred, average='weighted')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Logistic Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train set: (276, 8) (276,)\n",
      "Test set: (70, 8) (70,)\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "X_trainset, X_testset, y_trainset, y_testset = train_test_split( X, y, test_size=0.2, random_state=4)\n",
    "print ('Train set:', X_trainset.shape,  y_trainset.shape)\n",
    "print ('Test set:', X_testset.shape,  y_testset.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Jaccard Score ::  0.6857142857142857\n",
      "F1 Score ::  0.6670522459996144\n"
     ]
    }
   ],
   "source": [
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.metrics import confusion_matrix\n",
    "LR = LogisticRegression(C=0.01, solver='liblinear').fit(X_trainset,y_trainset)\n",
    "LR\n",
    "lr_predict = LR.predict(X_testset)\n",
    "lr_predict\n",
    "\n",
    "from sklearn.metrics import jaccard_similarity_score\n",
    "print(\"Jaccard Score :: \",jaccard_similarity_score(y_testset, lr_predict) )\n",
    "\n",
    "\n",
    "from sklearn.metrics import f1_score\n",
    "print(\"F1 Score :: \",f1_score(y_testset, lr_predict, average='weighted'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.5772287609479654"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lr_prob = LR.predict_proba(X_testset)\n",
    "\n",
    "from sklearn.metrics import log_loss\n",
    "log_loss(y_testset, lr_prob)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Model Evaluation using Test set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import jaccard_similarity_score\n",
    "from sklearn.metrics import f1_score\n",
    "from sklearn.metrics import log_loss"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First, download and load the test set:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--2019-09-26 16:57:15--  https://s3-api.us-geo.objectstorage.softlayer.net/cf-courses-data/CognitiveClass/ML0101ENv3/labs/loan_test.csv\n",
      "Resolving s3-api.us-geo.objectstorage.softlayer.net (s3-api.us-geo.objectstorage.softlayer.net)... 67.228.254.193\n",
      "Connecting to s3-api.us-geo.objectstorage.softlayer.net (s3-api.us-geo.objectstorage.softlayer.net)|67.228.254.193|:443... connected.\n",
      "HTTP request sent, awaiting response... 200 OK\n",
      "Length: 3642 (3.6K) [text/csv]\n",
      "Saving to: ‘loan_test.csv’\n",
      "\n",
      "100%[======================================>] 3,642       --.-K/s   in 0s      \n",
      "\n",
      "2019-09-26 16:57:15 (337 MB/s) - ‘loan_test.csv’ saved [3642/3642]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "!wget -O loan_test.csv https://s3-api.us-geo.objectstorage.softlayer.net/cf-courses-data/CognitiveClass/ML0101ENv3/labs/loan_test.csv"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "button": false,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "source": [
    "### Load Test set for evaluation "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "button": false,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Unnamed: 0.1</th>\n",
       "      <th>loan_status</th>\n",
       "      <th>Principal</th>\n",
       "      <th>terms</th>\n",
       "      <th>effective_date</th>\n",
       "      <th>due_date</th>\n",
       "      <th>age</th>\n",
       "      <th>education</th>\n",
       "      <th>Gender</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>PAIDOFF</td>\n",
       "      <td>1000</td>\n",
       "      <td>30</td>\n",
       "      <td>9/8/2016</td>\n",
       "      <td>10/7/2016</td>\n",
       "      <td>50</td>\n",
       "      <td>Bechalor</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>PAIDOFF</td>\n",
       "      <td>300</td>\n",
       "      <td>7</td>\n",
       "      <td>9/9/2016</td>\n",
       "      <td>9/15/2016</td>\n",
       "      <td>35</td>\n",
       "      <td>Master or Above</td>\n",
       "      <td>male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>21</td>\n",
       "      <td>21</td>\n",
       "      <td>PAIDOFF</td>\n",
       "      <td>1000</td>\n",
       "      <td>30</td>\n",
       "      <td>9/10/2016</td>\n",
       "      <td>10/9/2016</td>\n",
       "      <td>43</td>\n",
       "      <td>High School or Below</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>24</td>\n",
       "      <td>24</td>\n",
       "      <td>PAIDOFF</td>\n",
       "      <td>1000</td>\n",
       "      <td>30</td>\n",
       "      <td>9/10/2016</td>\n",
       "      <td>10/9/2016</td>\n",
       "      <td>26</td>\n",
       "      <td>college</td>\n",
       "      <td>male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>35</td>\n",
       "      <td>35</td>\n",
       "      <td>PAIDOFF</td>\n",
       "      <td>800</td>\n",
       "      <td>15</td>\n",
       "      <td>9/11/2016</td>\n",
       "      <td>9/25/2016</td>\n",
       "      <td>29</td>\n",
       "      <td>Bechalor</td>\n",
       "      <td>male</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0  Unnamed: 0.1 loan_status  Principal  terms effective_date  \\\n",
       "0           1             1     PAIDOFF       1000     30       9/8/2016   \n",
       "1           5             5     PAIDOFF        300      7       9/9/2016   \n",
       "2          21            21     PAIDOFF       1000     30      9/10/2016   \n",
       "3          24            24     PAIDOFF       1000     30      9/10/2016   \n",
       "4          35            35     PAIDOFF        800     15      9/11/2016   \n",
       "\n",
       "    due_date  age             education  Gender  \n",
       "0  10/7/2016   50              Bechalor  female  \n",
       "1  9/15/2016   35       Master or Above    male  \n",
       "2  10/9/2016   43  High School or Below  female  \n",
       "3  10/9/2016   26               college    male  \n",
       "4  9/25/2016   29              Bechalor    male  "
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_df = pd.read_csv('loan_test.csv')\n",
    "test_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "testAcc={}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/envs/Python36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1143: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no predicted samples.\n",
      "  'precision', 'predicted', average, warn_for)\n"
     ]
    }
   ],
   "source": [
    "svm_pred = clf.predict(X_testset)\n",
    "testAcc['SVM-JACCARD']=jaccard_similarity_score(y_testset, svm_pred)\n",
    "testAcc['SVM-F1-SCORE']=f1_score(y_testset, svm_pred, average= 'weighted')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "predTree = loanTree.predict(X_testset)\n",
    "testAcc['TREE-JACCARD']=jaccard_similarity_score( y_testset, predTree)\n",
    "testAcc['TREE-F1-SCORE']=f1_score( y_testset, predTree, average='weighted')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "knn_pred=neigh.predict(X_testset)\n",
    "testAcc['KNN-JACCARD']=jaccard_similarity_score(y_testset, knn_pred)\n",
    "testAcc['KNN-F1-SCORE']=f1_score( y_testset, knn_pred, average='weighted')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "lr_predict = LR.predict(X_testset)\n",
    "lr_prob = LR.predict_proba(X_testset)\n",
    "testAcc['lr-JACCARD']=jaccard_similarity_score(y_testset, lr_predict)\n",
    "testAcc['lr-F1-SCORE']=f1_score(y_testset, lr_predict, average='weighted')\n",
    "testAcc['lr-LogLoss']=log_loss(y_testset, lr_prob)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'SVM-JACCARD': 0.7857142857142857,\n",
       " 'TREE-F1-SCORE': 0.806433487849417,\n",
       " 'SVM-F1-SCORE': 0.6670522459996144,\n",
       " 'TREE-JACCARD': 0.8142857142857143,\n",
       " 'KNN-JACCARD': 0.7857142857142857,\n",
       " 'KNN-F1-SCORE': 0.7766540244416351,\n",
       " 'lr-JACCARD': 0.6857142857142857,\n",
       " 'SVM-LogLoss': 0.5772287609479654,\n",
       " 'lr-F1-SCORE': 0.6670522459996144,\n",
       " 'lr-LogLoss': 0.5772287609479654}"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "testAcc"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Report\n",
    "You should be able to report the accuracy of the built model using different evaluation metrics:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "| Algorithm          | Jaccard | F1-score | LogLoss |\n",
    "|--------------------|---------|----------|---------|\n",
    "| KNN                |0.7857   | 0.7766   | NA      |\n",
    "| Decision Tree      |0.814    | 0.8064   | NA      |\n",
    "| SVM                |0.7857   |0.6670    | NA      |\n",
    "| LogisticRegression |0.6857   |0.6670    |0.5772   |"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Worthy to note, better hyperparameters tuning can be used for better results"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "button": false,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "source": [
    "<h2>Want to learn more?</h2>\n",
    "\n",
    "IBM SPSS Modeler is a comprehensive analytics platform that has many machine learning algorithms. It has been designed to bring predictive intelligence to decisions made by individuals, by groups, by systems – by your enterprise as a whole. A free trial is available through this course, available here: <a href=\"http://cocl.us/ML0101EN-SPSSModeler\">SPSS Modeler</a>\n",
    "\n",
    "Also, you can use Watson Studio to run these notebooks faster with bigger datasets. Watson Studio is IBM's leading cloud solution for data scientists, built by data scientists. With Jupyter notebooks, RStudio, Apache Spark and popular libraries pre-packaged in the cloud, Watson Studio enables data scientists to collaborate on their projects without having to install anything. Join the fast-growing community of Watson Studio users today with a free account at <a href=\"https://cocl.us/ML0101EN_DSX\">Watson Studio</a>\n",
    "\n",
    "<h3>Thanks for completing this lesson!</h3>\n",
    "\n",
    "<h4>Author:  <a href=\"https://ca.linkedin.com/in/saeedaghabozorgi\">Saeed Aghabozorgi</a></h4>\n",
    "<p><a href=\"https://ca.linkedin.com/in/saeedaghabozorgi\">Saeed Aghabozorgi</a>, PhD is a Data Scientist in IBM with a track record of developing enterprise level applications that substantially increases clients’ ability to turn data into actionable knowledge. He is a researcher in data mining field and expert in developing advanced analytic methods like machine learning and statistical modelling on large datasets.</p>\n",
    "\n",
    "<hr>\n",
    "\n",
    "<p>Copyright &copy; 2018 <a href=\"https://cocl.us/DX0108EN_CC\">Cognitive Class</a>. This notebook and its source code are released under the terms of the <a href=\"https://bigdatauniversity.com/mit-license/\">MIT License</a>.</p>"
   ]
  }
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