DropoutNone

DropoutNone is a setting used in machine learning models to indicate that no dropout regularization is applied during training. Dropout is a technique that temporarily disables a random subset of neural network connections to prevent overfitting and improve generalization to new data. When DropoutNone is selected, the model trains without this additional randomness, allowing all connections to remain active throughout training. This can be useful in certain situations where preserving every connection is desirable or when the dataset is small enough that overfitting is less of a concern.