Exercise

Prediction and submission to DataHack

To upload a submission to DataHack, you need to predict the loan approval rate for the observations in the test set. This can be done using ".predict()" method with logistic regression object (model). To extract the test features we will need to create a numpy array of input features of test data set in the same way as we did when training the model for training data.

Next, you need to make sure your output is in line with the submission requirements of DataHack: a csv file with exactly 367 entries and two columns: LoanID and LoanStatus. Then create a csv file using to_csv() method from Pandas.

Instructions

100 XP

Store input variable in list "predictors"
Use .predict() method for prediction

Take Hint (-30 XP)