Problem statement Credit scoring algorithms, which makes a guess at the probability of default, are the method banks use to determine whether or not a loan should be granted. This guided project requires Learners to improve on the state of the art in credit scoring, by predicting the probability that somebody will experience financial distress in the next two years.
his is an imbalanced data set so we will learn to handle such a datset with different methods. In this project we will apply the following concepts:
train-test-split Handling missing values Standard scaler Logisitic Regression f1score,precisionscore,recall,confusion_matrix rocaucscore,rocaucplot SMOTE Random Forrest classifier