/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 vote313 views2 answers
Python can a imported module get variables from main module
Python
13 votes302 views2 answers
Year to datetime python
Python
0 vote408 views1 answer
Python REPL loop
Python
2 votes295 views1 answer
Discord.py username input in numbers
Python
0 vote358 views1 answer
ImportError: cannot import name 'MigrateCommand' from 'flask_migrate'
Python
2 votes327 views1 answer
Create pandas dataframe with random numbers
Python
16 votes343 views4 answers
List to dataframe columns
Python
0 vote403 views1 answer
How to create api for get data in django rest framework
Python Django
2 votes362 views1 answer
Mean python code
Python
1 vote365 views1 answer
Discord bot python on reaction
Python