1st Place Solution for CrowdFlower Product Search Results Relevance Competition on Kaggle.
1st Place Solution for Search Results Relevance Competition on Kaggle
The best single model we have obtained during the competition was an XGBoost model with linear booster of Public LB score 0.69322 and Private LB score 0.70768. Our final winning submission was a median ensemble of 35 best Public LB submissions. This submission scored 0.70807 on Public LB and 0.72189 on Private LB.
See ./Doc/Kaggle_CrowdFlower_ChenglongChen.pdf
for documentation.
./Data
.python ./Code/Feat/run_all.py
to generate features. This will take a few hours.python ./Code/Model/generate_best_single_model.py
to generate best single model submission. In our experience, it only takes a few trials to generate model of best performance or similar performance. See the training log in ./Output/Log/[Pre@solution]_[Feat@svd100_and_bow_Jun27]_[Model@reg_xgb_linear]_hyperopt.log
for example.python ./Code/Model/generate_model_library.py
to generate model library. This is quite time consuming. But you don't have to wait for this script to finish: you can run the next step once you have some models trained.
python ./Code/Model/generate_ensemble_submission.py
to generate submission via ensemble selection../Output/Subm
.