GitHub - hrishivib/credit-risk-score-prediction: This repo illustrate the example of credit score prediction using different algorithm model from sklearn for classifying whether the person have good or bad credit score.

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This repo illustrate the example of credit score prediction using different algorithm model from sklearn for classifying whether the person have good or bad credit score.

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Readme.txt		Readme.txt
credit_score_prediction.py		credit_score_prediction.py
test_data.csv		test_data.csv
train_data.csv		train_data.csv

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Problem statement:
Credit risk score prediction for the data which have different attribute type like 
- categorical and numerical(ratio), 
- potentially sensitive  or protected  attributes like gender, race, age. 
- dealing with imbalanced data like class labels with varying distribution 

Experimented with different machine learning algorithms by using sklearn package.


About code:
Function for decision tree is on line no. 68
Function for random forest is on line no. 129
Function for knn is on line no. 143
Function for gaussian naive bayes is on line no. 171
Function for xgboost classifier is on line no. 179

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This repo illustrate the example of credit score prediction using different algorithm model from sklearn for classifying whether the person have good or bad credit score.