# -*- coding: utf-8 -*-
"""
Created on Mon Jan 21 09:29:51 2019

@author: sunny
"""
import numpy as np
from sklearn import datasets
Iris = datasets.load_iris()
x = Iris.data
y=Iris.target

#df = pd.read_csv('https://archive.ics.uci.edu/ml/machine-learning-databases/Iris/Iris-data)
from sklearn.model_selection import train_test_split
x_train,x_test,y_train,y_test = train_test_split(x,y,test_size=0.2)

from sklearn.preprocessing import StandardScaler
sc = StandardScaler()
sc.fit(x_train)
x_train_std = sc.transform(x_train)
x_test_std = sc.transform(x_test)


from sklearn.linear_model import Perceptron
ppn = Perceptron(max_iter=40,eta0 = 0.1,random_state=0)
ppn.fit(x_train_std,y_train)

y_pred = ppn.predict(x_test_std)
print('Misclassified samples : %d '%(y_test !=y_pred).sum())

from sklearn.metrics import accuracy_score
print('Accuracy: %.2f'%accuracy_score(y_test,y_pred))