Rmse in python

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

Rmse in python

from sklearn.metrics import mean_squared_error
from math import sqrt

rms = sqrt(mean_squared_error(y_actual, y_predicted))

Source: stackoverflow.com

Similar codes

2 votes160 views2 answers
Numpy rolling average
Python
59 votes138 views3 answers
Join() python
Python
0 vote165 views1 answer
Python dijkstra implementation stack
Python
3 votes137 views1 answer
Factorial program
Python
0 vote131 views1 answer
Add Cog to bot in Discord.py
Python
1 vote147 views1 answer
Selenium text returns empty string python
Python
0 vote171 views1 answer
Python : read all the contents of the file into a string (use of 'with open')
Python
2 votes130 views3 answers
How to reboot a python script
Python
0 vote149 views1 answer
Input for competitive programming
Python
6 votes129 views1 answer
Save and load a dictionary python
Python