Ejemplo n.º 1
0
from preProcessor import PreProcessor
import argparse
from regression import Regression
from picDrawer import PicDrawer

if __name__ == '__main__':
    '''
    
        python run -f [filepath] -s [filepath] -c [stock code]
    
    output:
        stock error : implement by regression.score() 
        picture : implement by drawer
    
    '''

    # create pre processor

    data_cleaner = PreProcessor()
    train_feature, train_label, test_feature, test_label = data_cleaner.run()

    reg = Regression()
    reg.fit(train_feature, train_label)
    pred_result = reg.predict(test_feature)

    score = reg.score(test_label, pred_result)

    drawer = PicDrawer()
    drawer.run()
Ejemplo n.º 2
0
    args = parser.parse_args()

    file_path = args.filepath
    train_set_choice = args.train_set
    code = str(args.code)
    method = args.method

    # create pre processor
    data_cleaner = PreProcessor(train_set_choice, code, file_path, args.ratio,
                                args.preprocess)
    train_feature, train_label, test_feature, test_label, corr = data_cleaner.run(
    )
    print test_label
    reg = Regression(args.method)

    print "training model...\n"
    reg.fit(train_feature, train_label)
    print "predicting...\n"
    pred_result = reg.predict(test_feature)
    print "scoring...\n"
    score = reg.score(test_label, test_feature)

    print "drawing...\n"
    drawer = PicDrawer(corr, pred_result, test_label)
    drawer.get_corr_map()
    drawer.get_validation_comparison()

    print("score" + str(score))

    print "regressor exit!"