Theta values are not updating
code
def hypothesis(X,theta):
return theta[0]+theta[1]X
def error(X,y,theta):
m= X.shape[0]
error = 0
for i in range (m):
Hx= hypothesis(X[i],theta)
error += ((Hx-y[i])**2)
return error
def gradient(theta,X,y):
grad = np.zeros((2,))
m = X.shape[0]
for i in range (m):
Hx = hypothesis(X[i],theta)
grad[0] += Hx - y[i]
grad[1] += (Hx- y[i])X[i]
return grad
def GradientDescent(X,y,learning_rate = 0.001):
#theta = np.zeros((2,))
theta= np.array([-2.0,1.0])
itr = 0
error_list=[]
theta_list =[]
max_itr = 100
while (itr <=max_itr):
grad = gradient(theta,X,y)
e = error(X,y,theta)
error_list.append(e)
theta_list.append((theta[0],theta[1]))
theta[0] =theta[0]-learning_rategrad[0]
theta[1]= theta[1]-learning_rategrad[1]
itr+=1
return theta,error_list,theta_list
final_theta, error_list,theta_list = GradientDescent(X,y)
