Zillow-Prize
A repository of my code for the kaggle competition: Zillow Prize
Leaderboard
180/3799 (Top 5%)
Architecture
The final output is a weighted average of 4 models(Catboost, Genetic Programming, LightGBM, StackNet). StackNet is a great framework for ensembling models. For this competition, use 12 models for 5-fold stacking(level-2 model does not use level-1 model's features).
Some Thoughts and Tricks
- Kaggle community is very helpful. Learned a lot from shared kernels and discussion.
- Catboost seems to be the best single model for the competition.
- Feature engineering is important but I cannot come up with some "magic" features with combination of origin ones. Dropping some features is useful though.
- Choose different features for different models to increase the variety of models
- Ensemble as much irrelevent good models as possible. Tree-based models are suitable for kaggle competition, try different depth, loss, bagging strategy and etc.
- Cut off outliers with high |logerror|