def testSquaredError():
k = 5
data = Data(k, 0, 0)
data.importDataFromMat()
data.normalize()
sq = SquaredErrorLinearClassifier(2 ** 10, k)
sq.train(data.train_left, data.train_right, data.train_cat)
results, cat = sq.classify(data.test_left, data.test_right)
sq.confusion_matrix(cat, data.test_cat.argmax(axis=0))
err = Error()
err, misclass = err.norm_total_error(results.T, data.test_cat, k)
print "Error on the test set " + str(err)
print "Misclassification ratio on the test set " + str(misclass)
