Welcome to the in-class Kaggle competetion.
Do your best to make the best predictions by the closing time of the competition.
Write a report that indicates what you tried, what worked and what did not.
You will be scored based on your private and public leaderboard score but also on your creativity on trying various ideas.
This is a binary classification competition. The meanings of the features were not revealed by the data provider for privacy reasons.
The metric you are evaluated as is called Area Under the Curve (AUC). It is a binary accuracy metric that works well even for unbalanced problems. We will explain how the metric works in class.
File Descriptions
- train_final.csv - the training set
- test_final.csv - the test set
- sample-submission.csv - a sample submission file in the correct format.
Every row has an Id, an anonymous unique Identification given to each customer. Include the Id column in your predictions.