dropout: Dropout layer
In fdavidcl/ruta: Implementation of Unsupervised Neural Architectures
dropout R Documentation
Dropout layer
Description
Randomly sets a fraction rate of input units to 0 at each update during training
time, which helps prevent overfitting.
Usage
dropout(rate = 0.5)
Arguments
rate
The fraction of affected units
Value
A construct of class "ruta_network"
See Also
Other neural layers:
conv(),
dense(),
input(),
layer_keras(),
output(),
variational_block()
fdavidcl/ruta documentation built on July 5, 2023, 6:32 p.m.
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| dropout | R Documentation |
Dropout layer
Description
Randomly sets a fraction rate of input units to 0 at each update during training
time, which helps prevent overfitting.
Usage
dropout(rate = 0.5)
Arguments
rate |
The fraction of affected units |
Value
A construct of class "ruta_network"
See Also
Other neural layers:
conv(),
dense(),
input(),
layer_keras(),
output(),
variational_block()
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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