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unnir/share_my_cat.py

Created November 21, 2017 14:34
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share_my_cat.py
num_ensembles = 7
y_pred = 0.0
for i in tqdm(range(num_ensembles)):
model = CatBoostClassifier(random_seed = i+2, gradient_iterations = i+1 ,leaf_estimation_method ='Newton', learning_rate=0.057, l2_leaf_reg = 23, depth=6, od_pval=0.0000001, iterations = 920, loss_function='Logloss')
fit_model = model.fit(train_data)
y_pred += fit_model.predict_proba(test_data)[:,1]
y_pred /= num_ensembles
gc.collect()
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