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In this analysis, the credit risk dataset consisting of 32851 loan records to determine how best to predict whether or not a loan applicant will repay.

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Credit-Risk-Analysis

In this analysis, the credit risk dataset consisting of 32851 loan records to determine how best to predict whether or not a loan applicant will repay.

  • Libriries used: Pandas, numpy, matplotlib, seaborn, sklearn, imblearn.
  • Machine Learning models: LogisticRegression, DecisionTreeClassifier, XGBClassifier and XGBClassifier with GridSearchCV

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In this analysis, the credit risk dataset consisting of 32851 loan records to determine how best to predict whether or not a loan applicant will repay.

Topics

numpy scikit-learn pandas logistic-regression decision-tree-classifier gridsearchcv xgboost-classifier

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