Class and Description |
---|
BaseMultiLayerNetwork
A base class for a multi layer neural network with a logistic output layer
and multiple hidden layers.
|
Class and Description |
---|
LogisticRegression
Logistic regression implementation with jblas.
|
Class and Description |
---|
BaseNeuralNetwork
Baseline class for any Neural Network used
as a layer in a deep network such as an
DBN |
BaseNeuralNetwork.Builder |
NeuralNetwork
Single layer neural network, this is typically one that has
the objective function of reconstruction the input: also called feature detectors
|
Persistable |
Class and Description |
---|
Persistable |
Class and Description |
---|
BaseMultiLayerNetwork
A base class for a multi layer neural network with a logistic output layer
and multiple hidden layers.
|
BaseMultiLayerNetwork.Builder |
HiddenLayer
Vectorized Hidden Layer
|
NeuralNetwork
Single layer neural network, this is typically one that has
the objective function of reconstruction the input: also called feature detectors
|
Persistable |
Class and Description |
---|
BaseMultiLayerNetwork
A base class for a multi layer neural network with a logistic output layer
and multiple hidden layers.
|
BaseMultiLayerNetwork.Builder |
BaseNeuralNetwork
Baseline class for any Neural Network used
as a layer in a deep network such as an
DBN |
BaseNeuralNetwork.Builder |
HiddenLayer
Vectorized Hidden Layer
|
HiddenLayer.Builder |
LogisticRegression
Logistic regression implementation with jblas.
|
LogisticRegression.Builder |
NeuralNetwork
Single layer neural network, this is typically one that has
the objective function of reconstruction the input: also called feature detectors
|
NeuralNetwork.LossFunction
Which loss function to use
|
NeuralNetwork.OptimizationAlgorithm
Optimization algorithm to use
|
Persistable |
RectifiedLinearHiddenLayer
Rectified linear hidden units vs binomial sampled ones
|
RectifiedLinearHiddenLayer.Builder |
Class and Description |
---|
Persistable |
Class and Description |
---|
BaseMultiLayerNetwork
A base class for a multi layer neural network with a logistic output layer
and multiple hidden layers.
|
LogisticRegression
Logistic regression implementation with jblas.
|
NeuralNetwork
Single layer neural network, this is typically one that has
the objective function of reconstruction the input: also called feature detectors
|
NeuralNetwork.LossFunction
Which loss function to use
|
NeuralNetwork.OptimizationAlgorithm
Optimization algorithm to use
|
Class and Description |
---|
NeuralNetwork
Single layer neural network, this is typically one that has
the objective function of reconstruction the input: also called feature detectors
|
Class and Description |
---|
BaseNeuralNetwork
Baseline class for any Neural Network used
as a layer in a deep network such as an
DBN |
BaseNeuralNetwork.Builder |
NeuralNetwork
Single layer neural network, this is typically one that has
the objective function of reconstruction the input: also called feature detectors
|
NeuralNetwork.LossFunction
Which loss function to use
|
NeuralNetwork.OptimizationAlgorithm
Optimization algorithm to use
|
Persistable |
Class and Description |
---|
BaseMultiLayerNetwork
A base class for a multi layer neural network with a logistic output layer
and multiple hidden layers.
|
BaseMultiLayerNetwork.Builder |
BaseNeuralNetwork
Baseline class for any Neural Network used
as a layer in a deep network such as an
DBN |
NeuralNetwork
Single layer neural network, this is typically one that has
the objective function of reconstruction the input: also called feature detectors
|
NeuralNetwork.LossFunction
Which loss function to use
|
NeuralNetwork.OptimizationAlgorithm
Optimization algorithm to use
|
Persistable |
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