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This code generates the 1st place solution of Tradeshift Text Classification from our team "carl and snow"

https://www.kaggle.com/c/tradeshift-text-classification

It mainly includes two kinds of models:

  1. two-stage models using Xgboost and sklearn.
  2. online logistic regression.

Dependencies Python 2.7 pypy 2.4.0 Scikit learn-0.15.2 numpy 1.7.1 scipy 0.11.0 Xgboost 0.3

To generate a solution:

  1. Set Up all the dependencies
  2. change the data dir in run.py
  3. change the xgboost wrapper path in ./src/xgb_classifier.py
  4. python run.py

The best single solution: xgb-part1-d18-e0.09-min6-tree120-xgb_base.csv private LB 0.0044595

The best ensemble solution: best-solution.csv private LB 0.0043324 (1st place)

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This is the 1st place solution of a kaggle machine contest: Tradeshift Text Classification. http://www.kaggle.com/c/tradeshift-text-classification

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  • Python 100.0%