| L1 |
Minimize weight values |
from keras import regularizers |
http |
| L2 |
Minimize weight values. Bigger Values are heavier penalized compared to L1 |
from keras import regularizers |
http |
| Dropout |
Drop random neurons from a layer. Information needs to be encoded in multiple pathways. |
from keras.layers import Dropout |
http |
| Early-Stopping |
Stops the learning process if the score on the validation set stops improving. |
from keras.callbacks import EarlyStopping |
http |
| Limit layer size |
Reduce the complexity of the model to force abstraction of information. |
Reduce model size |
http |
| Data augmentation |
Augment the data to have a broader statistical variance and/or more data. |
E.g. adding noise, rotating images, handle punctuation, segmentation, annotate data, … |
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