Linear regression with normal equation

lin_reg_norm_eq.py

import numpy as np
import matplotlib.pyplot as plt


def plot_result(O):
    sample_size = 50
    linX = np.linspace(np.min(npdata[:,1]), np.max(npdata[:,1]), num=sample_size)
    testX = np.concatenate((np.ones((sample_size, 1)), linX.reshape((sample_size, 1))), axis=1)
    y = np.dot(testX, O)
    plt.plot(linX, y[:,0], 'r-')


if __name__ == '__main__':
    data = file("/Users/itarato/Desktop/weight.csv", 'r')
    npdata = np.genfromtxt(data, delimiter=',', skip_header=1)

    m = len(npdata)
    Y = npdata[:, 0].reshape((m, 1))

    plt.plot(npdata[:,1], npdata[:,0], 'b^')

    X = np.concatenate((np.ones((m, 1)), npdata[:, 1].reshape((m, 1))), axis=1)

    O = np.dot(np.dot(np.linalg.inv(np.dot(X.T, X)), X.T), Y)

    plot_result(O)
    plt.show()