def save_results(predictions, filename):
    with open(filename, 'w') as f:
        f.write("id,ACTION\n")
        for i, pred in enumerate(predictions):
            f.write("%d,%f\n" % (i + 1, pred))
Fit a single binary classifier.
dataset/ETHPy150Open kaz-Anova/ensemble_amazon/amazon_main_logit_3way.py/save_results--crossover with--dataset/ETHPy150Open scikit-learn/scikit-learn/sklearn/linear_model/stochastic_gradient.py/fit_binary