MSE Loss

neuralpy.loss_functions.MSELoss(reduction='mean')

info

MSE Loss is mostly stable and can be used for any project. In the future, any chance of breaking changes is very low.

Applies a Mean Squared Error loss function to the model.

For more information, check this page.

Supported Arguments

• reduction='mean' : (String) Specifies the reduction that is to be applied to the output.

Code Example

from neuralpy.models import Sequential

from neuralpy.optimizer import Adam

from neuralpy.loss_functions import MSELoss

...

# Rest of the imports

...

model = Sequential()

...

# Rest of the architecture

...

# Compiling the model

model.compile(optimizer=Adam(), loss_function=MSELoss(reduction='mean'))