rms error calculator in python

main.py
import numpy as np
import math

# defining actual and predicted values
actual = np.array([1, 2, 3, 4, 5])
predicted = np.array([1.5, 2.5, 3.5, 4.5, 5.5])

# calculating the squared error
squared_error = np.square(np.subtract(actual,predicted)).mean()

# calculating the root mean squared error
rms_error = math.sqrt(squared_error)

print("Root Mean Squared Error: ", rms_error)
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main.py
Root Mean Squared Error:  0.7071067811865476
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