Build a machine learning model that attempts to predict whether a loan from LendingClub will become high risk or not.
LendingClub is a peer-to-peer lending services company that allows individual investors to partially fund personal loans as well as buy and sell notes backing the loans on a secondary market. LendingClub offers their previous data through an API. Using this data to create machine learning models to classify the risk level of given loans. Specifically, comparing the Logistic Regression model and Random Forest Classifier.
- Convert categorical data to numeric
- Consider the models
- Create and compare two models on this data: a logistic regression, and a random forest classifier.
- Fit a LogisticRegression model and RandomForestClassifier model
The Random Forest Classifier Model after scaling performed better than the Logistic Regression model when scaled as previously predicted. The inital Random Forest Classifer training score was 0.79 and test score was 1.0.
LendingClub (2019-2020) Loan Stats. Retrieved from: https://resources.lendingclub.com/ https://medium.com/@amirmehrbakhsh/credit-scores-2-0-how-ai-and-machine-learning-will-revamp-how-we-evaluate-credit-worthiness-f97d5e1e6de1 https://medium.com/henry-jia/how-to-score-your-credit-1c08dd73e2ed