import sys
from sklearn import ensemble
from clean import clean_data
from predict import make_prediction


def fit_adaboost(X, y):
    clf = ensemble.AdaBoostClassifier(n_estimators=100)
    clf.fit(X, y)
    return clf


def main(argv):
    df_train = clean_data(argv[0])
    df_test = clean_data(argv[1])
    make_prediction(df_train, df_test, fit_adaboost,
        './output/prediction_ab.csv')


if __name__ == '__main__':
    main(sys.argv[1:])

0488942c802165efe36505e1f765cbdb0efb7d21
<mask token>


def fit_adaboost(X, y):
    clf = ensemble.AdaBoostClassifier(n_estimators=100)
    clf.fit(X, y)
    return clf


<mask token>

<mask token>


def fit_adaboost(X, y):
    clf = ensemble.AdaBoostClassifier(n_estimators=100)
    clf.fit(X, y)
    return clf


def main(argv):
    df_train = clean_data(argv[0])
    df_test = clean_data(argv[1])
    make_prediction(df_train, df_test, fit_adaboost,
        './output/prediction_ab.csv')


<mask token>

<mask token>


def fit_adaboost(X, y):
    clf = ensemble.AdaBoostClassifier(n_estimators=100)
    clf.fit(X, y)
    return clf


def main(argv):
    df_train = clean_data(argv[0])
    df_test = clean_data(argv[1])
    make_prediction(df_train, df_test, fit_adaboost,
        './output/prediction_ab.csv')


if __name__ == '__main__':
    main(sys.argv[1:])

import sys
from sklearn import ensemble
from clean import clean_data
from predict import make_prediction


def fit_adaboost(X, y):
    clf = ensemble.AdaBoostClassifier(n_estimators=100)
    clf.fit(X, y)
    return clf


def main(argv):
    df_train = clean_data(argv[0])
    df_test = clean_data(argv[1])
    make_prediction(df_train, df_test, fit_adaboost,
        './output/prediction_ab.csv')


if __name__ == '__main__':
    main(sys.argv[1:])
