Python save_predictions Examples

Example #1

def make_submission(network, params, u):
    print('Prepare submission')
    test = Dataset.from_test()
    if params.pca:
        X2 = test.get_pca_features(u)
    else:
        X2 = test.get_features()
    predictions = network.predict(X2)
    save_predictions(predictions, test.df)

Example #2

File: nn.py Project: klangner/telstra

def make_submission(network, params, u):
    print('Prepare submission')
    test = Dataset.from_test()
    if params.pca:
        X2 = test.get_pca_features(u)
    else:
        X2 = test.get_features()
    predictions = network.predict(X2)
    save_predictions(predictions, test.df)

Example #3

File: random_forrest.py Project: fenggami/NetworkPrediction

def prepare_solution():
    train = Dataset.from_train()
    X = train.get_features()
    Y = train.get_labels()
    rf = RandomForestRegressor(n_jobs=-1)
    model = rf.fit(X, Y)
    print('Train dataset score: %f' % loss(Y, model.predict(X)))
    test = Dataset.from_test()
    X2 = test.get_features()
    Y2 = model.predict(X2)
    save_predictions(Y2, test.df)

Example #4

File: random_forrest.py Project: klangner/telstra

def prepare_solution():
    train = Dataset.from_train()
    X = train.get_features()
    Y = train.get_labels()
    rf = RandomForestRegressor(n_jobs=-1)
    model = rf.fit(X, Y)
    print('Train score: %f' % loss(Y, model.predict(X)))
    test = Dataset.from_test()
    X2 = test.get_features()
    Y2 = model.predict(X2)
    save_predictions(Y2, test)