import numpy as numpy
import pandas as pd
import matplotlib.pyplot as plt

dataset = pd.read_csv('Social_Network_Ads.csv')
x = dataset.iloc[:, [2, 3]].values
y = dataset.iloc[:, 4].values


from sklearn.cross_validation import train_test_split
x_train, x_test, y_train, y_test = train_test_split(x, y, test_size = 0.25, random_state = 0)

from sklearn.preprocessing import StandardScaler
sc = StandardScaler()
x_train = sc.fit_transform(x_train)
x_test = sc.transform(x_test)

from sklearn.svm import SVC
classifier = SVC(kernel = 'rbf', random_state = 0)
classifier.fit(x_train, y_train)


y_pred = classifier.predict(x_test)


from sklearn.metrics import confusion_matrix
cm = confusion_matrix(y_test, y_pred)
 
from matplotlib.colors import ListedColormap
x_set,y_set=x_train,y_train
x1,x2=np.meshgrid(np.arrange(start=x_set[:,0].min()-1,stop=x_set[:,0].max()+1,step=0.01),
                  np.mesggrid(np.arrange(start=x_set[:,1].min()-1,stop=x_set[:,1].max()+1,step=0.01)
plt.contourf(x1,x2,classifier.predict(np.array([x1.ravel(),x2.ravel()]).T).reshape(x1.shape),
             alpha=0.75,cmap=ListedColormap(('red','green')))
plt.xlim(x1.min(), x1.max())
plt.ylim(x2.min(), x2.max())
for i, j in enumerate(np.unique(y_set)):
    plt.scatter(x_set[y_set == j, 0], x_set[y_set == j, 1],
                c = ListedColormap(('red', 'green'))(i), label = j)
plt.title('Kernel SVM (Training set)')
plt.xlabel('Age')
plt.ylabel('Estimated Salary')
plt.legend()
plt.show()

from matplotlib.colors import Listedcolormap
x_set,y_set=x_test,y_test
x1,x2=np.meshgrid(np.arrange(start=x.set[:,0].min()-1,stop=x.set[:,0].max()+1.step=0.01),
                  np.meshgrid(start=x.set[:,1].min()-1,stop=x_set[:,1].max()+1,step=0.01))
plt.contourf(x1, x2, classifier.predict(np.array([x1.ravel(), x2.ravel()]).T).reshape(x1.shape),
             alpha = 0.75, cmap = ListedColormap(('red', 'green'))
plt.xlim(x1.min(),x1.max())
plt.ylim(x2.min(), x2.max())
for i,j in enumerate(np.unique(y_set)):
    plt.scatter(x_set[y_set == j, 0], x_set[y_set == j, 1],
                c = ListedColormap(('red', 'green'))(i), label = j)
plt.title('Kernel SVM (Training set)')
plt.xlabel('Age')
plt.ylabel('Estimated Salary')    plt.scatter(x_set[y_set == j, 0], x_set[y_set == j, 1],
                c = ListedColormap(('red', 'green'))(i), label = j)
plt.title('Kernel SVM (Training set)')
plt.xlabel('Age')
plt.ylabel('Estimated Salary')
plt.legend()
plt.show()
plt.legend()
plt.show()