kaggle-otto2
Our 20th place solution of the Kaggle OTTO – Multi-Objective Recommender System competition
Code Structure
Solution Summary
Solution details are written in the Kaggle Discussion: https://www.kaggle.com/competitions/otto-recommender-system/discussion/382771
3 Types of experiment environment
My code has 3 expriment environemt
- dev: For faster local experiment. With 1/20 sampled cv data (e.g.
./yaml/exp001_dev.yaml
) - cv: For local experiment and validation (e.g.
./yaml/exp001_cv.yaml
) - lb: For submission (e.g.
./yaml/exp001_lb.yaml
)
Procedure
Please see ./demo.ipynb
for the execution log example
000. Setup poetry
# Install packages
poetry install
# Get into virtual env
poetry shell
000. Download datasets
# Download datasets
# ※ ~/kaggle/.kaggle.json with your Kaggle API Key is required
./bin/000_download.sh
001. Preprocess
./bin/001_preprocess.sh exp001_dev
002. Candidate Generation
./bin/002_candidate_generation.sh exp001_dev
003. Feature Engineering
./bin/003_feature_engineering.sh exp001_dev
004. Train Ranker
./bin/004_train_ranker.sh exp001_dev lgbm