Flight delays
Predict whether a flight will be delayed for more than 15 minutes.
In this assignment, you’re asked to beat a baseline in the “Flight delays” competition. This time we decided to share a pretty decent CatBoost baseline, you’ll have to improve the provided solution. Prior to working on the assignment, you’d better check out the corresponding course material: Classification, Decision Trees and k Nearest Neighbors, the same as an interactive web-based Kaggle Kernel Ensembles: Bagging, the same as a Kaggle Kernel Random Forest, the same as a Kaggle Kernel Feature Importance, the same as a Kaggle Kernel Gradient boosting, the same as a Kaggle Kernel Logistic regression, Random Forest, and LightGBM in the “Kaggle Forest Cover Type Prediction” competition: Kernel You can also practice with demo assignments, which are simpler and already shared with solutions: “Decision trees with a toy task and the UCI Adult dataset”: assignment + solution “Logistic Regression and Random Forest in the credit scoring problem”: assignment + solution There are also 7 video lectures on trees, forests, boosting and their applications: mlcourse.ai/video mlcourse.ai tutorials on categorical feature encoding (by Wayde Herman) and CatBoost (by Mikhail Tribunskiy) Last but not the least: Public Kernels in this competition Your task is to: beat “A2 baseline (10 credits)” on Public LB (0.75914 LB score) rename your team in full accordance with A1 and the course rating (to appear on 16.09.2019)
