averaged_perceptron.py

import numpy as np
def perceptron(features,labels):
    theta=np.array([0]*len(features[0]))
    theta0=0
    t=10
    count=1
    sum_theta=theta
    sum_theta_0=theta0
    while(t):
        t=t-1
        for i in range(len(features)):
            if (np.dot(features[i],theta)+theta0)*labels[i]<=0:
                #print('mistake')
                theta=theta+np.multiply(labels[i],features[i])
                theta0=theta0+labels[i]
            sum_theta=sum_theta+theta
            sum_theta_0=sum_theta_0_theta_0
            count+=1
        #print(theta)
        #We return Average theta value and Average theta0 value
    return (list(theta/count),theta0/count)
if __name__=="__main__":
    x=[[1,2],[2,3],[3,4],[4,5]]
    features=x
    y=[1,1,-1,-1]
    theta,theta0=perceptron(features,y)
    print('theta={},theta0={}'.format(theta,theta0))