/Loan-prediction-using-Decision-Tree-Model-and-Random-Forest-Model

In this i have analysed and visualized the loan dataset and converted its categorical feature like purpose of taking the loan to the dummies and trained the dataset using Decision Tree Model and Random Forest model then i have perform prediction on test data for both Decision tree model and Random forest model separately In Random forest model i have no. of estimators(Trees) as 350 on comparison of classification report it was observed that Random forest did it better

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Loan-prediction-using-Decision-Tree-Model-and-Random-Forest-

In this i have analysed and visualized the loan dataset and converted its categorical feature like purpose of taking the loan to the dummies and trained the dataset using Decision Tree Model and Random Forest model then i have perform prediction on test data for both Decision tree model and Random forest model separately In Random forest model i have no. of estimators(Trees) as 350 on comparison of classification report it was observed that Random forest did it better

Decision Tree:- classification report-------------

      precision           recall  f1-score   support
      

      0                    0.86      0.82      0.84      2431
      1                    0.20      0.25      0.22       443

avg / total 0.75
0.73
0.74
2874

Random Forest:- classification report--------------

      precision           recall  f1-score   support
      

      0                   0.85      1.00      0.92      2431
      1                   0.47      0.02      0.03       443

avg / total 0.79
0.85
0.78
2874