Uses of Class
de.jungblut.classification.nn.MultilayerPerceptron.MultilayerPerceptronBuilder

Packages that use MultilayerPerceptron.MultilayerPerceptronBuilder

Package	Description
de.jungblut.classification.nn

Uses of MultilayerPerceptron.MultilayerPerceptronBuilder in de.jungblut.classification.nn

Methods in de.jungblut.classification.nn that return MultilayerPerceptron.MultilayerPerceptronBuilder

Modifier and Type	Method and Description
MultilayerPerceptron.MultilayerPerceptronBuilder	MultilayerPerceptron.MultilayerPerceptronBuilder.batchParallelism(int numThreads)
static MultilayerPerceptron.MultilayerPerceptronBuilder	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	MultilayerPerceptron.MultilayerPerceptronBuilder.hiddenLayerDropout(double d) Sets the hidden layer dropout probability.
MultilayerPerceptron.MultilayerPerceptronBuilder	MultilayerPerceptron.MultilayerPerceptronBuilder.inputLayerDropout(double d) Sets the input layer dropout probability.
MultilayerPerceptron.MultilayerPerceptronBuilder	MultilayerPerceptron.MultilayerPerceptronBuilder.lambda(double lambda) Sets the regularization parameter lambda, defaults to 0 if not set.
MultilayerPerceptron.MultilayerPerceptronBuilder	MultilayerPerceptron.MultilayerPerceptronBuilder.miniBatchSize(int size)
MultilayerPerceptron.MultilayerPerceptronBuilder	MultilayerPerceptron.MultilayerPerceptronBuilder.stochastic() Sets the training mode to stochastic.
MultilayerPerceptron.MultilayerPerceptronBuilder	MultilayerPerceptron.MultilayerPerceptronBuilder.stochastic(boolean stochastic) If verbose is true, stochastic training will be used.
MultilayerPerceptron.MultilayerPerceptronBuilder	MultilayerPerceptron.MultilayerPerceptronBuilder.trainingType(TrainingType type) Sets the training type, it defaults to CPU- so only use if you want to use the GPU.
MultilayerPerceptron.MultilayerPerceptronBuilder	MultilayerPerceptron.MultilayerPerceptronBuilder.verbose() Sets verbose to true.
MultilayerPerceptron.MultilayerPerceptronBuilder	MultilayerPerceptron.MultilayerPerceptronBuilder.verbose(boolean verbose) If verbose is true, progress indicators will be printed to STDOUT.
MultilayerPerceptron.MultilayerPerceptronBuilder	MultilayerPerceptron.MultilayerPerceptronBuilder.withWeights(WeightMatrix[] weights) Sets the initial weights, maybe from an already trained network, or from a fancy random initialization technique.