The purpose of this analysis was to utilize credit card datasets from an actual company (LendingClub) and use linear regression to sample and predict the data. The data was oversampled through the use of the RandomOverSampler and SMOTE algorithms, while it was under sampled using the ClusterCentroids algorithm. After obtaining the results, The BalancedRandomForestClassifier and EasyEnsembleClassifier models were utilized to predict credit risk.
Undersampling
Oversampling
Smote Oversampling
Combination Sampling
RandomForestClassifier
