here is my code :-
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
def readData(filename):
df = pd.read_csv(filename)
return df.values
x = readData("./Linear_X_Train.csv")
y = readData("./Linear_Y_Train.csv")
#print(x.shape)
#print(y.shape)
#plt.scatter(x,y)
x = x.reshape(3750,)
y = y.reshape(3750,)
X = (x-x.mean())/(x.std())
Y = y
#plt.scatter(X,Y)
#plt.show()
def hypothesis(theta,x):
return theta[0]+theta[1]*x
def error(X,Y,theta):
total_error = 0
m = X.shape[0]
for i in range(m):
total_error += (hypothesis(theta,X[i])-Y[i])**2
return 0.5*total_error
def gradient(X,Y,theta):
grad=np.zeros((2,))
m=X.shape[0]
for i in range(m):
grad[0]+=(hypothesis(theta,X[i])-Y[i])
grad[1]+=(hypothesis(theta,X[i])-Y[i])*X[i]
return grad
def gradientDescent(X,Y,learning_rate,maxItr):
grad=np.zeros((2,))
theta=np.zeros((2,))
error_list = []
for i in range(maxItr):
grad=gradient(X,Y,theta)
e = error(X,Y,theta)
error_list.append(e)
theta[0] = theta[0] - learning_rategrad[0]
theta[1] = theta[1] - learning_rategrad[1]
return theta,error_list
final_theta,error_list = gradientDescent(X,Y,learning_rate=0.001,maxItr=1000)
#print(theta[0],theta[1])
plt.scatter(X,Y)
plt.plot(X,hypothesis(final_theta,X),color=“g”)
#plt.plot(error_list)
plt.show()
I’m getting error in this code of this type…
