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How to square the individual matrix value using python?

I am trying to implement the Cost function in python.

Assume my data have X (loading from txt file)
and my theta value is [[0]
[0]]
For that I have implemented as below:

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from scipy.linalg import fractional_matrix_power
load_data = pd.read_csv('C:python_programex1data1.txt',sep = ",",header = None)
feature_vale = load_data[0]
y = np.matrix(load_data[1])
m = len(feature_vale)
#print(m)
#plt.scatter(load_data[0],load_data[1])
df = pd.DataFrame(pd.Series(1,index= range(0,m)))
df[1] = load_data[0]
X = np.matrix(df)
row_theta = np.zeros(2,dtype = int)
theta = np.array([row_theta]) # Transpose the array
print(theta.T)
prediction = np.matmul(X,theta.T)
error = (prediction-y)
print(error)


Output of the error I got as expected(Compare with Matlab and Octiva):

[[-17.592 -9.1302 -13.662 ... -0.14454 -9.0551 -0.61705]
[-17.592 -9.1302 -13.662 ... -0.14454 -9.0551 -0.61705]
[-17.592 -9.1302 -13.662 ... -0.14454 -9.0551 -0.61705]
...
...
[-17.592 -9.1302 -13.662 ... -0.14454 -9.0551 -0.61705]
[-17.592 -9.1302 -13.662 ... -0.14454 -9.0551 -0.61705]
[-17.592 -9.1302 -13.662 ... -0.14454 -9.0551 -0.61705]]


But next step I need to square the individual value of the matrix.

I have tired the following commands to square the individual value of the matrix,still I am not able to get the expected result as per matlab.

sqerror = np.float_power(error,2.0,where=True)
print(sqerror)


sqerror = np.np.power(error,2.0)
print(sqerror)



sqerror = np.square(error)
print(sqerror)

Output:
[[3.09478464e+02 8.33605520e+01 1.86650244e+02 ... 2.08918116e-02
8.19948360e+01 3.80750702e-01]
[3.09478464e+02 8.33605520e+01 1.86650244e+02 ... 2.08918116e-02
8.19948360e+01 3.80750702e-01]
[3.09478464e+02 8.33605520e+01 1.86650244e+02 ... 2.08918116e-02
8.19948360e+01 3.80750702e-01]
...
...
[3.09478464e+02 8.33605520e+01 1.86650244e+02 ... 2.08918116e-02
8.19948360e+01 3.80750702e-01]
[3.09478464e+02 8.33605520e+01 1.86650244e+02 ... 2.08918116e-02
8.19948360e+01 3.80750702e-01]
[3.09478464e+02 8.33605520e+01 1.86650244e+02 ... 2.08918116e-02
8.19948360e+01 3.80750702e-01]]


But expected value of first element is :

-17.592 * -17.592 = 309.478464
-9.1302 * -9.1302 = 83.360552


Please help to resolve the above issue

Data reference:https://searchcode.com/codesearch/view/5404318/

1 Answer
1

repeat the following steps and let me know

error_matrix = np.asmatrix(error)
error_square = np.square(error_matrix)


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