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()
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!"