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perceptron.py
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perceptron.py
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#!/usr/bin/env python
# coding: utf-8
"""
author -- ToxaZ
Coursera Machine Learning Introduction 2nd week assignement
5 - https://www.coursera.org/learn/vvedenie-mashinnoe-obuchenie/programming/w7Rqc/normalizatsiia-priznakov
"""
import pandas as pd
from sklearn.linear_model import Perceptron
from sklearn.metrics import accuracy_score
from sklearn.preprocessing import StandardScaler
from utils import write_submission
def get_accuracy(X_train, y_train, X_test, y_test):
clf = Perceptron(random_state=241)
clf.fit(X_train, y_train)
y_predictions = clf.predict(X_test)
return accuracy_score(y_test, y_predictions)
def main():
data = {}
scaler = StandardScaler()
for data_type in ['train', 'test']:
df = pd.read_csv('data/perceptron-{0}.csv'.format(data_type),
header=None)
data['X_' + data_type] = df.iloc[:, 1:].values
data['y_' + data_type] = df.iloc[:, 0].values
data['X_train_scaled'] = scaler.fit_transform(data['X_train'])
data['X_test_scaled'] = scaler.transform(data['X_test'])
acc = get_accuracy(data['X_train'], data['y_train'],
data['X_test'], data['y_test'],)
acc_scaled = get_accuracy(data['X_train_scaled'], data['y_train'],
data['X_test_scaled'], data['y_test'])
write_submission(round(abs(acc - acc_scaled), 3), '51')
if __name__ == '__main__':
main()