run.py

import numpy as np
from src.ensemble_log_regression import Config, EnsembleClassifiers, LogisticClassifier
from src.utils import dataloader, standardize, create_csv_submission, build_polynomial


def main():
    x, y = dataloader(mode='train', reduced=False)
    x_test = dataloader(mode='test', reduced=False)
    '''For the dataloader there are two modes train and test, depending on the dataset loaded.'''
    x = standardize(x)
    x_test = standardize(x_test)
    config = Config(batch_size=120, num_epochs=400, learning_rate=5 * 10 ** -4,
                    lambda_=2.15443469003e-05, mode='train')
    log_class = LogisticClassifier(config, (build_polynomial(x), y))
    log_class.train(show_every=10)
    predictions_test = log_class.predict_submission(log_class(build_polynomial(x_test)))

    create_csv_submission(np.arange(350000, 350000 + x_test.shape[0]), predictions_test,
                          'dataset/submission_0x.csv')

if __name__ == '__main__':
    main()