Predicting Credit Risk

Background

A machine learning model was built to attempt to predict whether a loan would be approved or not. A comparison was made between the Logistic Regression model and Random Forest Classifier.

Steps

• Used Pandas to import the data (lending_data.csv) located in the Resources folder
• Made a prediction as to which model would perform better
• Created a Logistic Regression model, fit it to the data, and printed the model's score
• Created a Random Forest Classifier model, fit it to the data, and printed the model's score
• Wrote results and compared results to prediction