zygmuntz / Adversarial Validation
Licence: mit
Creating a better validation set when test examples differ from training examples
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python
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Adversarial validation
The santander dir holds the scripts for the Santander competition:
distinguish_train_test.py - try to distinguish train/test set examples
validate.py - get validation AUC scores for logistic regression and random forest
predict.py - output test predictions from logistic regression and random forest
Similarly, the 'numerai' dir contains the Numerai scripts:
distinguish_train_test.py - try to distinguish train/test set examples
sort_train.py - sort training examples by their similarity to test examples
validate_sorted.py - get validation scores using for most test-like examples
predict.py - output test predictions
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