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kaggle_iceberg_ship

useful links:

notebooks

base models

other_hand_features

generate images features and use lr,rf,gbrt,xgb,lgb generate base features

ensemble

ensemble features and submit

stacking

test stacking methods like voting, works for public LB

my final result

  • run ensemble/xgb_ensemble-all.ipynb

  • copy results/all_xgb_sub_fold_5_rnd66.csv to stacking/all_xgb_sub_fold_5_rnd_66local1318.csv

  • run stacking/best_median_v4.ipynb

  • get results/stack_minmax_bestbase5.csv ( public score 0.1228, private score 0.1400 )

  • final rank 258/3341, top 8%, my first kaggle medal !!! 😜

leaderboard link

https://www.kaggle.com/c/statoil-iceberg-classifier-challenge/leaderboard

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