public static final class MultilayerPerceptron.MultilayerPerceptronBuilder extends Object
Classifier| Modifier and Type | Method and Description |
|---|---|
MultilayerPerceptron.MultilayerPerceptronBuilder |
batchParallelism(int numThreads) |
MultilayerPerceptron |
build() |
static MultilayerPerceptron.MultilayerPerceptronBuilder |
create(int[] layer,
ActivationFunction[] activations,
LossFunction errorFunction,
Minimizer minimizer,
int maxIteration)
Creates a new TrainingConfiguration with the mandatory configurations of
the activation functions, the to be used minimizer and the maximum
iterations.
|
MultilayerPerceptron.MultilayerPerceptronBuilder |
hiddenLayerDropout(double d)
Sets the hidden layer dropout probability.
|
MultilayerPerceptron.MultilayerPerceptronBuilder |
inputLayerDropout(double d)
Sets the input layer dropout probability.
|
MultilayerPerceptron.MultilayerPerceptronBuilder |
lambda(double lambda)
Sets the regularization parameter lambda, defaults to 0 if not set.
|
MultilayerPerceptron.MultilayerPerceptronBuilder |
miniBatchSize(int size) |
MultilayerPerceptron.MultilayerPerceptronBuilder |
stochastic()
Sets the training mode to stochastic.
|
MultilayerPerceptron.MultilayerPerceptronBuilder |
stochastic(boolean stochastic)
If verbose is true, stochastic training will be used.
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MultilayerPerceptron.MultilayerPerceptronBuilder |
trainingType(TrainingType type)
Sets the training type, it defaults to CPU- so only use if you want to
use the GPU.
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MultilayerPerceptron.MultilayerPerceptronBuilder |
verbose()
Sets verbose to true.
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MultilayerPerceptron.MultilayerPerceptronBuilder |
verbose(boolean verbose)
If verbose is true, progress indicators will be printed to STDOUT.
|
MultilayerPerceptron.MultilayerPerceptronBuilder |
withWeights(WeightMatrix[] weights)
Sets the initial weights, maybe from an already trained network, or from
a fancy random initialization technique.
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public MultilayerPerceptron.MultilayerPerceptronBuilder trainingType(TrainingType type)
public MultilayerPerceptron.MultilayerPerceptronBuilder lambda(double lambda)
public MultilayerPerceptron.MultilayerPerceptronBuilder verbose()
public MultilayerPerceptron.MultilayerPerceptronBuilder verbose(boolean verbose)
public MultilayerPerceptron.MultilayerPerceptronBuilder hiddenLayerDropout(double d)
public MultilayerPerceptron.MultilayerPerceptronBuilder inputLayerDropout(double d)
public MultilayerPerceptron.MultilayerPerceptronBuilder withWeights(WeightMatrix[] weights)
public MultilayerPerceptron.MultilayerPerceptronBuilder miniBatchSize(int size)
size - the minibatch size to use. Batches are calculated in parallel
on every cpu core if not overridden by
batchParallelism(int).public MultilayerPerceptron.MultilayerPerceptronBuilder batchParallelism(int numThreads)
numThreads - set the number of threads where batches should be
calculated in parallel.public MultilayerPerceptron.MultilayerPerceptronBuilder stochastic()
public MultilayerPerceptron.MultilayerPerceptronBuilder stochastic(boolean stochastic)
public MultilayerPerceptron build()
MultilayerPerceptron with the given configuration.public static MultilayerPerceptron.MultilayerPerceptronBuilder create(int[] layer, ActivationFunction[] activations, LossFunction errorFunction, Minimizer minimizer, int maxIteration)
layer - the number of neurons for each layer, each index denotes a
layer.activations - the activation functions to be used, each index
denotes a layer.errorFunction - the error function on the last layer.minimizer - the minimizer to be used.maxIterations - how many iterations (epochs) to run.Copyright © 2016. All rights reserved.