Robust_Regression.py

import numpy as np
import matplotlib.pyplot as plt  # To visualize
import pandas as pd  # To read data
from sklearn.linear_model import RANSACRegressor
from sklearn.linear_model import LinearRegression

data = pd.read_csv('housing.csv')  # load data set
X = data.iloc[:, 0].values.reshape(-1, 1)  # values converts it into a numpy array
Y = data.iloc[:, 1].values.reshape(-1, 1)  # -1 means that calculate the dimension of rows, but have 1 column
robust_regressor = RANSACRegressor()  # create object for the class
robust_regressor.fit(X,Y)  # perform robust regression
Y_pred = robust_regressor.predict(X)  # make predictions

plt.scatter(X, Y)
plt.plot(X, Y_pred, color='red')
plt.show()