proj1_helpers.py
No OneTemporary
Actions

Subscribers

None

File Metadata

	# -- coding: utf-8 --
	"""some helper functions for project 1."""
	import csv
	import numpy as np


	def load_csv_data(data_path, sub_sample=False):
	"""Loads data and returns y (class labels), tX (features) and ids (event ids)"""
	y = np.genfromtxt(data_path, delimiter=",", skip_header=1, dtype=str, usecols=1)
	x = np.genfromtxt(data_path, delimiter=",", skip_header=1)
	ids = x[:, 0].astype(np.int)
	input_data = x[:, 2:]

	# convert class labels from strings to binary (-1,1)
	yb = np.ones(len(y))
	yb[np.where(y=='b')] = -1

	# sub-sample
	if sub_sample:
	yb = yb[::50]
	input_data = input_data[::50]
	ids = ids[::50]

	return yb, input_data, ids


	def predict_labels(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)] = -1
	y_pred[np.where(y_pred > 0)] = 1

	return y_pred


	def create_csv_submission(ids, y_pred, name):
	"""
	Creates an output file in csv format for submission to kaggle
	Arguments: ids (event ids associated with each prediction)
	y_pred (predicted class labels)
	name (string name of .csv output file to be created)
	"""
	with open(name, 'w') as csvfile:
	fieldnames = ['Id', 'Prediction']
	writer = csv.DictWriter(csvfile, delimiter=",", fieldnames=fieldnames)
	writer.writeheader()
	for r1, r2 in zip(ids, y_pred):
	writer.writerow({'Id':int(r1),'Prediction':int(r2)})