/Python/From sklearn.metrics import mean_square_error

From sklearn.metrics import mean_square_error

How to calculate rmse in linear regression python

actual = [0, 1, 2, 0, 3]
predicted = [0.1, 1.3, 2.1, 0.5, 3.1]

mse = sklearn.metrics.mean_squared_error(actual, predicted)

rmse = math.sqrt(mse)

print(rmse)

Calculate root mean square error python

def rmse(predictions, targets):
    return np.sqrt(((predictions - targets) ** 2).mean())

Source: stackoverflow.com

From sklearn.metrics import mean_square_error

import mean_squared_error

Similar codes

-1 vote292 views1 answer
K means clustering python medium
Python
0 vote305 views1 answer
How to cycle a list in python
Python
1 vote308 views1 answer
Gimp python
Python
0 vote285 views1 answer
Run exe for python and wait until finish
Python
0 vote259 views1 answer
How to create a custom function in python
Python
-1 vote276 views2 answers
If __name__ == '__main__': a = int(input()) b = int(input())
Python
1 vote309 views1 answer
Yesno django
Python Django
1 vote306 views2 answers
How to print out text in python
Python
0 vote322 views1 answer
Django blog new post
Python Django
0 vote270 views7 answers
Convert python to java online
Python