Logistic Regression / Customer Information / Return Matrix / Model Applying
When customers went to a bank for loan business, bank will evalueate the payment ability of customers, which is the important reference for making decision that whether to lend money to customers. If the evalueation system shows that a customer having a good income condation, bank will lend money to her or him, otherwise the loan aplication will be reject. But sometimes the evalueation system could make some mistake, such as mark a high score for those haven't the payment ability, which would bring lost for bank. So in order to reduce the probability of these unexpectable consenqunse to zero limitly, bank must find a perfect and precise model, which is also our project goal. So we will create a better model using the customer loaning history, with the asistance from sklearn-package and python, to make the profit of bank loan business maximized.