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Copy_of_support_vector_regression.ipynb

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+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "name": "Copy of support_vector_regression.ipynb",
+      "provenance": [],
+      "collapsed_sections": [],
+      "toc_visible": true,
+      "include_colab_link": true
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "view-in-github",
+        "colab_type": "text"
+      },
+      "source": [
+        "<a href=\"https://colab.research.google.com/github/amansoni24/Regression/blob/main/Copy_of_support_vector_regression.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "m3PAEPRDRLA3"
+      },
+      "source": [
+        "# Support Vector Regression (SVR)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "0VCUAVIjRdzZ"
+      },
+      "source": [
+        "## Importing the libraries"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "56oRF-QfSDzC"
+      },
+      "source": [
+        "import numpy as np\n",
+        "import matplotlib.pyplot as plt\n",
+        "import pandas as pd"
+      ],
+      "execution_count": 4,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "fXVXoFWtSF4_"
+      },
+      "source": [
+        "## Importing the dataset"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "xfoa8OSORfHQ"
+      },
+      "source": [
+        "dataset = pd.read_csv('Data.csv')\n",
+        "X = dataset.iloc[:, :-1].values\n",
+        "y = dataset.iloc[:, -1].values"
+      ],
+      "execution_count": 5,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "_8Ny1GfPiV3m"
+      },
+      "source": [
+        "y = y.reshape(len(y),1)"
+      ],
+      "execution_count": 6,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "6Vk3nNlrCVCN"
+      },
+      "source": [
+        "## Splitting the dataset into the Training set and Test set"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "x_fXqrziCV3_"
+      },
+      "source": [
+        "from sklearn.model_selection import train_test_split\n",
+        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.2, random_state = 0)"
+      ],
+      "execution_count": 7,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "YS8FeLHYS-nI"
+      },
+      "source": [
+        "## Feature Scaling"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "PGeAlD1HTDI1"
+      },
+      "source": [
+        "from sklearn.preprocessing import StandardScaler\n",
+        "sc_X = StandardScaler()\n",
+        "sc_y = StandardScaler()\n",
+        "X_train = sc_X.fit_transform(X_train)\n",
+        "y_train = sc_y.fit_transform(y_train)"
+      ],
+      "execution_count": 8,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "eiU6D2QFRjxY"
+      },
+      "source": [
+        "## Training the SVR model on the Training set"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "y6R4rt_GRz15",
+        "outputId": "21dcbd44-743a-47d6-d02a-39b34b5af75f",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        }
+      },
+      "source": [
+        "from sklearn.svm import SVR\n",
+        "regressor = SVR(kernel = 'rbf')\n",
+        "regressor.fit(X_train, y_train)"
+      ],
+      "execution_count": 9,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "/usr/local/lib/python3.6/dist-packages/sklearn/utils/validation.py:760: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().\n",
+            "  y = column_or_1d(y, warn=True)\n"
+          ],
+          "name": "stderr"
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "SVR(C=1.0, cache_size=200, coef0=0.0, degree=3, epsilon=0.1, gamma='scale',\n",
+              "    kernel='rbf', max_iter=-1, shrinking=True, tol=0.001, verbose=False)"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 9
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "aPYA5W1pDBOE"
+      },
+      "source": [
+        "## Predicting the Test set results"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "vSqFVDYrDROW",
+        "outputId": "9f10a8af-1407-4e51-f338-baab8d46bfab",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        }
+      },
+      "source": [
+        "y_pred = sc_y.inverse_transform(regressor.predict(sc_X.transform(X_test)))\n",
+        "np.set_printoptions(precision=2)\n",
+        "print(np.concatenate((y_pred.reshape(len(y_pred),1), y_test.reshape(len(y_test),1)),1))"
+      ],
+      "execution_count": 10,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "[[434.05 431.23]\n",
+            " [457.94 460.01]\n",
+            " [461.03 461.14]\n",
+            " ...\n",
+            " [470.6  473.26]\n",
+            " [439.42 438.  ]\n",
+            " [460.92 463.28]]\n"
+          ],
+          "name": "stdout"
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "CMsYlps2DX1d"
+      },
+      "source": [
+        "## Evaluating the Model Performance"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "HxsRWlURDr6S",
+        "outputId": "9e671c8f-26c6-4107-b7b8-6775dfa8d4f6",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        }
+      },
+      "source": [
+        "from sklearn.metrics import r2_score\n",
+        "r2_score(y_test, y_pred)"
+      ],
+      "execution_count": 11,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "0.9480784049986258"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 11
+        }
+      ]
+    }
+  ]
+}