Created
March 24, 2020 21:38
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import numpy as np | |
def perceptron(features,labels): | |
theta=np.array([0]*len(features[0])) | |
theta0=0 | |
t=10 | |
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] | |
#print(theta) | |
return (list(theta),theta0) | |
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)) |
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