create_submission.py
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	import numpy as np
	from proj1_helpers import *
	from functions import *
	import datetime

	def predict_labels_modified(weights, data):
	"""Generates class predictions given weights, and a test data matrix"""
	y_pred = np.dot(data, weights)
	y_pred[np.where(y_pred <= 0.5)] = -1
	y_pred[np.where(y_pred > 0.5)] = 1

	return y_pred


	def normalize2(x, x_helper):
	minimum = min(np.min(x),np.min(x_helper))
	maximum = max(np.max(x),np.max(x_helper))

	range_x = maximum - minimum

	x -= minimum

	x = x/range_x

	return x

	#y_tr, x_tr_noisy, ids_tr = load_csv_data("train.csv")
	#y_te,x_te,ids_te = load_csv_data("test.csv")

	x_tr1 = real_mean(x_tr)
	x_te1 = real_mean2(x_te,x_tr)#format_data2(xx,x_tr_noisy)

	x_te_touse = normalize2(x_te1,x_tr1)

	tx_te = np.c_[np.ones((yy.shape[0], 1)),x_te_touse]

	y_pred = predict_labels(w_final, tx_te)

	create_csv_submission(ids_te, y_pred, "new_submission")