/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

0 vote220 views1 answer
Couchbase python
Python
0 vote199 views1 answer
Python3 subprocess getoutput
Python
2 votes218 views2 answers
Import other python files
Python
1 vote211 views3 answers
Sequencia de fibonacci python
Python
0 vote265 views1 answer
Nth catalan number
Python
11 votes191 views3 answers
How to convert a list into string with \n
Python
1 vote175 views2 answers
Flask link style in static
Python Flask
1 vote204 views1 answer
Data structures and algorithms in python
Python
1 vote196 views3 answers
Program to draw rectangle in python
Python
0 vote212 views2 answers
Displaying flash message django
Python Django