/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

6 votes308 views2 answers
How to add mouse button in pygame
Python
0 vote312 views1 answer
Which clause is used to place condition with GROUP BY clause in a table
Python
7 votes302 views1 answer
PIL discord
Python
0 vote314 views1 answer
How to convert linked list to list in python
Python
0 vote327 views1 answer
Python generator in while loop
Python
0 vote303 views2 answers
Torch.unsqueeze
Python
-2 votes318 views1 answer
Discord python send private message
Python
2 votes297 views1 answer
How to replace a word in csv file using python
Python
1 vote332 views1 answer
Create dict from two lists
Python
0 vote305 views1 answer
90/360
Python