SVR

#reading the data
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd

dataset=pd.read_csv('Position_Salaries.csv')
X=dataset.iloc[:,1:2].values
Y=dataset.iloc[:, 2].values

#scaling 
from sklearn.preprocessing import StandardScaler
sc_X = StandardScaler()
sc_Y = StandardScaler()
X = sc_X.fit_transform(X)
Y = sc_Y.fit_transform(Y)

#fitting the SVR

from sklearn.svm import SVR
regressor=SVR(kernel='rbf')
regressor.fit(X,Y)

#predict 
y_predict=sc_Y.inverse_transform(regressor.predict(sc_X.transform(np.array[[6.5]])))

#plot svr
plt.scatter(X,Y,color='red')
plt.plot(X,regressor.predict(X),color='blue')
plt.xlabel('levels')
plt.ylabel('salary')
plt.title('truth or bluff(linear regresson)')
plt.show()