GitHub - rahulrksmau/Sklearn: Python ML models

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Name		Name	Last commit message	Last commit date
Latest commit History 2 Commits
Decision Tree.ipynb		Decision Tree.ipynb
GBM model.ipynb		GBM model.ipynb
Linear Regression.ipynb		Linear Regression.ipynb
Logical Regression.ipynb		Logical Regression.ipynb
Parameter_Tuning_GBM Data Processing.ipynb		Parameter_Tuning_GBM Data Processing.ipynb
ReadME		ReadME
Test.csv		Test.csv
Train.csv		Train.csv
Untitled.ipynb		Untitled.ipynb
test_modified.csv		test_modified.csv
train_modified.csv		train_modified.csv

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Loan Submission Machine Learning Problem (Analytical Vidya) : This Challenge is the prediction of whether a customer will pay his loads or not. This problem contain data of customer’s knowledge and last loan submission history, based on that model will predict he/she will pay his/her loans on time or not.

Model used : Supervise Learning GBM, Decision Tree, Logical and Linear Regression. 
Datasets : https://github.com/rahulrksmau/Sklearn/blob/master/Test.csv , https://github.com/rahulrksmau/Sklearn/blob/master/Train.csv
Link : https://github.com/rahulrksmau/Sklearn

Steps done : creation of modified test and train dataset using feature engineering and data cleaning , model training, testing over train dataset, model accuracy, predicting the result for actual dataset at last creation of submission csv. 
Result :  GBM 79.5%
Decision Tree 96.6%
Logical Regression 98.5%
Linear Regression 19%