This is a binary classification model to predict credit card approvals. Models evaluated - Two-Class Boosted Decision Tree model, Two-Class Neural Network Two-Class Logistic Regression
After loading up the credit card data, columns are selected. Key, Ethnicity, Male(Gender), and Drivers License are excluded from the model. Then the data is cleaned up. 5% of the data (37 entries) are missing data and are removed from the data set. After setting categorical variables and label (predictor), the data set is split 70:30 into training and test data. Then the 3 models are trained, scored and evaluated.