A B C D E F G H I L M N O P R S T U V W 

A

AbstractFeedforwardNet - Class in org.cognity.neural.net
This class implements a feedforward neural network.
AbstractFeedforwardNet(Layer, Layer, Set<Layer>, Set<Link>, List<Layer>) - Constructor for class org.cognity.neural.net.AbstractFeedforwardNet
 
AbstractMatlabIO - Class in org.cognity.data.io
The base class for MatlabImporter and MatlabExporter.
AbstractMatlabIO() - Constructor for class org.cognity.data.io.AbstractMatlabIO
 
AbstractMatlabIO.Orientation - Enum in org.cognity.data.io
The orientation of data samples in the matrix.
AbstractNeuralNet - Class in org.cognity.neural.net
Base class for all neural networks.
AbstractNeuralNet(Layer, Layer, Set<Layer>, Set<Link>) - Constructor for class org.cognity.neural.net.AbstractNeuralNet
Creates an instance of a neural network.
activate() - Method in class org.cognity.neural.layer.GenericTransferLayer
 
activate() - Method in class org.cognity.neural.layer.InputLayer
Doesn't do anything.
activate() - Method in interface org.cognity.neural.layer.Layer
Performs calculations for this layer.
activate() - Method in interface org.cognity.neural.link.Link
Performs computations for this link.
activate() - Method in class org.cognity.neural.link.WeightedLink
 
add(DataExample) - Method in class org.cognity.data.ListDataSet
 
addAll(Collection<? extends DataExample>) - Method in class org.cognity.data.ListDataSet
 
addCustom(int, Function) - Method in class org.cognity.neural.net.MlpNet.Builder
Adds a layer with specified size and activation function.
addLinear(int) - Method in class org.cognity.neural.net.MlpNet.Builder
Adds a layer with specified size and identity function as the activation function.
addSigmoid(int) - Method in class org.cognity.neural.net.MlpNet.Builder
Adds a layer with specified size and sigmoid function as the activation function.
addStep(int) - Method in class org.cognity.neural.net.MlpNet.Builder
Adds a layer with specified size and Heaviside step function as the activation function.
addTanh(int) - Method in class org.cognity.neural.net.MlpNet.Builder
Adds a layer with specified size and hyperbolic tangent as the activation function.

B

Backpropagation - Class in org.cognity.neural.train
The backpropagation algorithm with momentum.
Backpropagation(FeedforwardNet) - Constructor for class org.cognity.neural.train.Backpropagation
Creates a new object using default learning rate and momentum values.
Backpropagation(FeedforwardNet, double, double) - Constructor for class org.cognity.neural.train.Backpropagation
Creates a new object using provided learning rate and momentum values.
BipolarStep - Class in org.cognity.math.functions
Implements the bipolar step function.
BipolarStep() - Constructor for class org.cognity.math.functions.BipolarStep
 
build() - Method in class org.cognity.neural.net.MlpNet.Builder
Returns a new multilayer perceptron.
build() - Method in interface org.cognity.neural.net.NeuralNetBuilder
Returns the neural network object.

C

clear() - Method in class org.cognity.data.ListDataSet
 
compute(double[]) - Method in class org.cognity.neural.net.AbstractFeedforwardNet
 
compute(double[]) - Method in interface org.cognity.neural.net.NeuralNet
Performs computations for this network.
contains(Object) - Method in class org.cognity.data.ListDataSet
 
containsAll(Collection<?>) - Method in class org.cognity.data.ListDataSet
 

D

DataExample - Class in org.cognity.data
A data example is a basic data structure used during neural network training.
DataExample(double[]) - Constructor for class org.cognity.data.DataExample
Creates an unsupervised data example with specified input vector.
DataExample(double[], double[]) - Constructor for class org.cognity.data.DataExample
Creates a supervised data example with specified input and target vector.
DataSet - Interface in org.cognity.data
A data set is an ordered collection of unique data examples.
DataSetExporter - Interface in org.cognity.data.io
The interface for objects which export data sets to a file or some other data storage system.
DataSetImporter - Interface in org.cognity.data.io
The interface for objects which import data sets from some data storage system.
DEFAULT_INPUTS_NAME - Static variable in class org.cognity.data.io.AbstractMatlabIO
 
DEFAULT_LEARNING_RATE - Static variable in class org.cognity.neural.train.GradientDescent
The default learning rate.
DEFAULT_MAX_ERROR - Static variable in class org.cognity.neural.train.MaxErrorCondition
 
DEFAULT_MAX_ITERATIONS - Static variable in class org.cognity.neural.train.MaxIterationCondition
 
DEFAULT_MIN_ERROR_CHANGE - Static variable in class org.cognity.neural.train.MinErrorChangeCondition
 
DEFAULT_MOMENTUM - Static variable in class org.cognity.neural.train.GradientDescent
The default momentum.
DEFAULT_ORIENTATION - Static variable in class org.cognity.data.io.AbstractMatlabIO
 
DEFAULT_PARAM - Static variable in class org.cognity.math.functions.FastGaussian
 
DEFAULT_PARAM - Static variable in class org.cognity.math.functions.FastSigmoid
 
DEFAULT_PARAM - Static variable in class org.cognity.math.functions.Gaussian
 
DEFAULT_PARAM - Static variable in class org.cognity.math.functions.Linear
 
DEFAULT_PARAM - Static variable in class org.cognity.math.functions.Sigmoid
 
DEFAULT_TARGETS_NAME - Static variable in class org.cognity.data.io.AbstractMatlabIO
 

E

equals(Object) - Method in class org.cognity.data.DataExample
Two data examples are equal if and only if input and target vectors are equal.
equals(Object) - Method in class org.cognity.data.ListDataSet
 
equals(Object) - Method in class org.cognity.math.functions.BipolarStep
Two functions are equal if they return the same values for all possible arguments.
equals(Object) - Method in class org.cognity.math.functions.FastGaussian
Two functions are equal if they return the same values for all possible arguments.
equals(Object) - Method in class org.cognity.math.functions.FastSigmoid
Two functions are equal if they return the same values for all possible arguments.
equals(Object) - Method in class org.cognity.math.functions.FastTanh
Two functions are equal if they return the same values for all possible arguments.
equals(Object) - Method in class org.cognity.math.functions.Gaussian
Two functions are equal if they return the same values for all possible arguments.
equals(Object) - Method in class org.cognity.math.functions.Identity
Two functions are equal if they return the same values for all possible arguments.
equals(Object) - Method in class org.cognity.math.functions.Linear
Two functions are equal if they return the same values for all possible arguments.
equals(Object) - Method in class org.cognity.math.functions.Sigmoid
Two functions are equal if they return the same values for all possible arguments.
equals(Object) - Method in class org.cognity.math.functions.Tanh
Two functions are equal if they return the same values for all possible arguments.
equals(Object) - Method in class org.cognity.neural.link.WeightedLink
 
exportData(DataSet) - Method in interface org.cognity.data.io.DataSetExporter
 
exportData(DataSet) - Method in class org.cognity.data.io.MatlabExporter
Exports specified data set to the file.

F

fastExp(double) - Static method in class org.cognity.util.MathUtil
Calculates exp(arg) function value using a fast approximation.
FastGaussian - Class in org.cognity.math.functions
Fast implementation of the gaussian function which is defined as:
%resolution{160} $f(x) = e^{\frac{-x^{2}}{2 \cdot \sigma^{2}}}$
Where $\sigma$ is a constant defined by user.
FastGaussian() - Constructor for class org.cognity.math.functions.FastGaussian
 
FastGaussian(double) - Constructor for class org.cognity.math.functions.FastGaussian
 
FastSigmoid - Class in org.cognity.math.functions
Implements a sigmoid function defined as follows:
$f(x) = \frac{1}{1+e^{-\beta \cdot x}}$
Where $\beta$ is a constant defined by user.
FastSigmoid() - Constructor for class org.cognity.math.functions.FastSigmoid
 
FastSigmoid(double) - Constructor for class org.cognity.math.functions.FastSigmoid
 
FastTanh - Class in org.cognity.math.functions
Fast implementation of the hyperbolic tangent function, which is defined as follows:
$tanh(x) = 1 - \frac{2}{1+e^{2 \cdot x}}$
It calculates approximated value of exp(x) function, instead of using standard Math.exp method.
FastTanh() - Constructor for class org.cognity.math.functions.FastTanh
 
FeedforwardNet - Interface in org.cognity.neural.net
A feedforward neural network is a neural network where connections between the units do not form a directed cycle.
Function - Interface in org.cognity.math.functions
Represents a real-valued function $\mathbb{R} \rightarrow \mathbb{R}$.

G

Gaussian - Class in org.cognity.math.functions
Implements the gaussian function defined as:
%resolution{160} $f(x) = e^{\frac{-x^{2}}{2 \cdot \sigma^{2}}}$
Where $\sigma$ is a constant defined by user.
Gaussian() - Constructor for class org.cognity.math.functions.Gaussian
 
Gaussian(double) - Constructor for class org.cognity.math.functions.Gaussian
 
GenericTransferLayer - Class in org.cognity.neural.layer
The basic implementation of the TransferLayer interface.
GenericTransferLayer(int, Function) - Constructor for class org.cognity.neural.layer.GenericTransferLayer
Creates a new layer with specified number of neurons and transfer function.
get(int) - Method in interface org.cognity.data.DataSet
Returns a data example at specified position.
get(int) - Method in class org.cognity.data.ListDataSet
 
getBias(int) - Method in class org.cognity.neural.layer.GenericTransferLayer
 
getBias(int) - Method in interface org.cognity.neural.layer.TransferLayer
Returns the bias value of the specified neuron.
getCurrentError() - Method in class org.cognity.neural.train.GradientDescent
Returns the error value after the last iteration.
getCurrentIteration() - Method in class org.cognity.neural.train.GradientDescent
 
getCurrentIteration() - Method in interface org.cognity.neural.train.IterativeProcess
Returns the current iteration.
getDeriv(double) - Method in class org.cognity.math.functions.BipolarStep
 
getDeriv(double) - Method in class org.cognity.math.functions.FastGaussian
 
getDeriv(double) - Method in class org.cognity.math.functions.FastSigmoid
 
getDeriv(double) - Method in class org.cognity.math.functions.FastTanh
 
getDeriv(double) - Method in interface org.cognity.math.functions.Function
Returns a value of the first derivative of the function for the given argument.
getDeriv(double) - Method in class org.cognity.math.functions.Gaussian
 
getDeriv(double) - Method in class org.cognity.math.functions.Identity
 
getDeriv(double) - Method in class org.cognity.math.functions.Linear
 
getDeriv(double) - Method in class org.cognity.math.functions.Sigmoid
 
getDeriv(double) - Method in class org.cognity.math.functions.Tanh
 
getInput() - Method in class org.cognity.data.DataExample
Returns a reference to the input vector.
getInput(int) - Method in class org.cognity.neural.layer.GenericTransferLayer
 
getInput(int) - Method in class org.cognity.neural.layer.InputLayer
 
getInput(int) - Method in interface org.cognity.neural.layer.Layer
Returns the value of net input of the specified neuron.
getInputLayer() - Method in class org.cognity.neural.net.AbstractNeuralNet
 
getInputLayer() - Method in interface org.cognity.neural.net.NeuralNet
Returns the input layer of this network.
getInputLinks(Layer) - Method in class org.cognity.neural.net.AbstractNeuralNet
 
getInputLinks(Layer) - Method in interface org.cognity.neural.net.NeuralNet
Returns input links of the specified layer.
getInputMatrixName() - Method in class org.cognity.data.io.AbstractMatlabIO
Returns the name for the input matrix.
getInputSize() - Method in class org.cognity.data.DataExample
Returns the size of the input vector.
getInputSize() - Method in interface org.cognity.data.DataSet
Returns the size of input vectors in this data set.
getInputSize() - Method in class org.cognity.data.ListDataSet
 
getInputSize() - Method in class org.cognity.neural.net.AbstractNeuralNet
 
getInputSize() - Method in interface org.cognity.neural.net.NeuralNet
Returns the size of the input layer.
getLastError() - Method in class org.cognity.neural.train.GradientDescent
Returns the error value before the last iteration.
getLayerCount() - Method in class org.cognity.neural.net.AbstractNeuralNet
 
getLayerCount() - Method in interface org.cognity.neural.net.NeuralNet
Returns the number of all layers in this network.
getLayers() - Method in class org.cognity.neural.net.AbstractNeuralNet
 
getLayers() - Method in interface org.cognity.neural.net.NeuralNet
Returns a set of all layers in this network.
getLearningRate() - Method in class org.cognity.neural.train.GradientDescent
Returns the learning rate value.
getLinks() - Method in class org.cognity.neural.net.AbstractNeuralNet
 
getLinks() - Method in interface org.cognity.neural.net.NeuralNet
Returns a set of all links in this network.
getMomentum() - Method in class org.cognity.neural.train.GradientDescent
Returns the momentum value.
getNetwork() - Method in class org.cognity.neural.train.Backpropagation
 
getNetwork() - Method in interface org.cognity.neural.train.TrainingRule
Returns a network trained by this rule.
getNeuronCount() - Method in class org.cognity.neural.layer.GenericTransferLayer
 
getNeuronCount() - Method in class org.cognity.neural.layer.InputLayer
 
getNeuronCount() - Method in interface org.cognity.neural.layer.Layer
Returns the number of neurons in this layer.
getOneInputLink(Layer) - Method in class org.cognity.neural.net.AbstractNeuralNet
 
getOneInputLink(Layer) - Method in interface org.cognity.neural.net.NeuralNet
Returns one of input links of the specified layer.
getOneOutputLink(Layer) - Method in class org.cognity.neural.net.AbstractNeuralNet
 
getOneOutputLink(Layer) - Method in interface org.cognity.neural.net.NeuralNet
Returns one of output links of the specified layer.
getOrderedLayers() - Method in class org.cognity.neural.net.AbstractFeedforwardNet
 
getOrderedLayers() - Method in interface org.cognity.neural.net.FeedforwardNet
Returns a list of all layers in the network.
getOrientation() - Method in class org.cognity.data.io.AbstractMatlabIO
Returns the orientation of the data vectors in the matrix.
getOutput(int) - Method in class org.cognity.neural.layer.GenericTransferLayer
 
getOutput(int) - Method in class org.cognity.neural.layer.InputLayer
 
getOutput(int) - Method in interface org.cognity.neural.layer.Layer
Returns the value of the output of the specified neuron.
getOutputLayer() - Method in class org.cognity.neural.net.AbstractNeuralNet
 
getOutputLayer() - Method in interface org.cognity.neural.net.NeuralNet
Returns the output layer of this network.
getOutputLinks(Layer) - Method in class org.cognity.neural.net.AbstractNeuralNet
 
getOutputLinks(Layer) - Method in interface org.cognity.neural.net.NeuralNet
Returns output links of the specified layer.
getOutputSize() - Method in class org.cognity.neural.net.AbstractNeuralNet
 
getOutputSize() - Method in interface org.cognity.neural.net.NeuralNet
Returns the size of the output layer.
getParam() - Method in class org.cognity.math.functions.FastGaussian
Returns the sigma parameter.
getParam() - Method in class org.cognity.math.functions.FastSigmoid
Returns the beta parameter
getParam() - Method in class org.cognity.math.functions.Gaussian
Returns the sigma parameter.
getParam() - Method in class org.cognity.math.functions.Linear
 
getParam() - Method in interface org.cognity.math.functions.ParametrizedFunction
Returns the parameter of this function.
getParam() - Method in class org.cognity.math.functions.Sigmoid
 
getSource() - Method in interface org.cognity.neural.link.Link
Returns a source layer.
getSource() - Method in class org.cognity.neural.link.WeightedLink
 
getStopCondition() - Method in class org.cognity.neural.train.GradientDescent
 
getStopCondition() - Method in interface org.cognity.neural.train.IterativeProcess
Returns a stop condition for this process.
getStopReason() - Method in class org.cognity.neural.train.OrCondition
Returns the first satisfied condition.
getTarget() - Method in class org.cognity.data.DataExample
Returns a reference to the target output vector.
getTarget() - Method in interface org.cognity.neural.link.Link
Return the target layer.
getTarget() - Method in class org.cognity.neural.link.WeightedLink
 
getTargetMatrixName() - Method in class org.cognity.data.io.AbstractMatlabIO
Returns the name for the target matrix.
getTargetSize() - Method in class org.cognity.data.DataExample
Returns the size of the target output vector.
getTargetSize() - Method in interface org.cognity.data.DataSet
Return the size of target vectors in this data set.
getTargetSize() - Method in class org.cognity.data.ListDataSet
 
getTransferFunc() - Method in class org.cognity.neural.layer.GenericTransferLayer
Returns the activation function of this layer.
getTransferFunc() - Method in interface org.cognity.neural.layer.TransferLayer
Returns the transfer function of this layer.
getValue(double) - Method in class org.cognity.math.functions.BipolarStep
 
getValue(double) - Method in class org.cognity.math.functions.FastGaussian
 
getValue(double) - Method in class org.cognity.math.functions.FastSigmoid
 
getValue(double) - Method in class org.cognity.math.functions.FastTanh
 
getValue(double) - Method in interface org.cognity.math.functions.Function
Returns a value of the function for the given argument.
getValue(double) - Method in class org.cognity.math.functions.Gaussian
 
getValue(double) - Method in class org.cognity.math.functions.Identity
 
getValue(double) - Method in class org.cognity.math.functions.Linear
 
getValue(double) - Method in class org.cognity.math.functions.Sigmoid
 
getValue(double) - Method in class org.cognity.math.functions.Tanh
 
getWeight(int, int) - Method in interface org.cognity.neural.link.Link
Returns a weight between toNeuron-th neuron in the target layer and fromNeuron-th neuron in the source layer.
getWeight(int, int) - Method in class org.cognity.neural.link.WeightedLink
 
getWeightCount() - Method in interface org.cognity.neural.link.Link
Returns the number of weights in this link.
getWeightCount() - Method in class org.cognity.neural.link.WeightedLink
 
GradientDescent - Class in org.cognity.neural.train
The base class for gradient descent algorithms.
GradientDescent() - Constructor for class org.cognity.neural.train.GradientDescent
Creates a new gradient descent algorithm using default learning rate and momentum values.

H

hasDeriv() - Method in class org.cognity.math.functions.BipolarStep
 
hasDeriv() - Method in class org.cognity.math.functions.FastGaussian
 
hasDeriv() - Method in class org.cognity.math.functions.FastSigmoid
 
hasDeriv() - Method in class org.cognity.math.functions.FastTanh
 
hasDeriv() - Method in interface org.cognity.math.functions.Function
Returns true if the function is differentiable.
hasDeriv() - Method in class org.cognity.math.functions.Gaussian
 
hasDeriv() - Method in class org.cognity.math.functions.Identity
 
hasDeriv() - Method in class org.cognity.math.functions.Linear
 
hasDeriv() - Method in class org.cognity.math.functions.Sigmoid
 
hasDeriv() - Method in class org.cognity.math.functions.Tanh
 
hashCode() - Method in class org.cognity.data.DataExample
 
hashCode() - Method in class org.cognity.data.ListDataSet
 
hashCode() - Method in class org.cognity.math.functions.BipolarStep
 
hashCode() - Method in class org.cognity.math.functions.FastGaussian
 
hashCode() - Method in class org.cognity.math.functions.FastSigmoid
 
hashCode() - Method in class org.cognity.math.functions.FastTanh
 
hashCode() - Method in class org.cognity.math.functions.Gaussian
 
hashCode() - Method in class org.cognity.math.functions.Identity
 
hashCode() - Method in class org.cognity.math.functions.Linear
 
hashCode() - Method in class org.cognity.math.functions.Sigmoid
 
hashCode() - Method in class org.cognity.math.functions.Tanh
 
hashCode() - Method in class org.cognity.neural.link.WeightedLink
 
hasInputLinks(Layer) - Method in class org.cognity.neural.net.AbstractNeuralNet
 
hasInputLinks(Layer) - Method in interface org.cognity.neural.net.NeuralNet
Returns true if the specified layer has at least one input link.
hasOutputLinks(Layer) - Method in class org.cognity.neural.net.AbstractNeuralNet
 
hasOutputLinks(Layer) - Method in interface org.cognity.neural.net.NeuralNet
Returns true if the specified layer has at least one output link.

I

Identity - Class in org.cognity.math.functions
Implements the identity function:
$f(x) = x$
Identity() - Constructor for class org.cognity.math.functions.Identity
 
importData() - Method in interface org.cognity.data.io.DataSetImporter
 
importData() - Method in class org.cognity.data.io.MatlabImporter
Imports the data set.
init(Layer) - Method in interface org.cognity.neural.init.LayerInitializer
Initializes ordinary layer.
init(TransferLayer) - Method in interface org.cognity.neural.init.LayerInitializer
Initializes transfer layer.
init(NeuralNet) - Method in interface org.cognity.neural.init.NeuralNetInitializer
Initializes specified network.
init(NeuralNet) - Method in class org.cognity.neural.init.UniformInitializer
 
init(LayerInitializer) - Method in class org.cognity.neural.layer.GenericTransferLayer
 
init(LayerInitializer) - Method in class org.cognity.neural.layer.InputLayer
 
init(LayerInitializer) - Method in interface org.cognity.neural.layer.Layer
Initializes this layer using the provided initializer.
initialize() - Method in class org.cognity.neural.net.AbstractNeuralNet
 
InputLayer - Class in org.cognity.neural.layer
Input layer is a layer which provides data for other layers.
InputLayer(int) - Constructor for class org.cognity.neural.layer.InputLayer
Creates a new input layer with specified number of neurons.
isEmpty() - Method in class org.cognity.data.ListDataSet
 
isNotSatisfied() - Method in class org.cognity.neural.train.MaxErrorCondition
 
isNotSatisfied() - Method in class org.cognity.neural.train.MaxIterationCondition
 
isNotSatisfied() - Method in class org.cognity.neural.train.MinErrorChangeCondition
 
isNotSatisfied() - Method in class org.cognity.neural.train.OrCondition
 
isNotSatisfied() - Method in interface org.cognity.neural.train.StopCondition
Returns true is this condition is not satisfied.
isSatisfied() - Method in class org.cognity.neural.train.MaxErrorCondition
 
isSatisfied() - Method in class org.cognity.neural.train.MaxIterationCondition
 
isSatisfied() - Method in class org.cognity.neural.train.MinErrorChangeCondition
 
isSatisfied() - Method in class org.cognity.neural.train.OrCondition
 
isSatisfied() - Method in interface org.cognity.neural.train.StopCondition
Returns true is this condition is satisfied.
isSupervised() - Method in class org.cognity.data.DataExample
Returns true if this data example is supervised.
isSupervised() - Method in interface org.cognity.data.DataSet
Returns true if this data set is supervised.
isSupervised() - Method in class org.cognity.data.ListDataSet
 
IterativeProcess - Interface in org.cognity.neural.train
The iterative process is a process which repeats some action in each iteration until certain stop condition is met.
iterator() - Method in class org.cognity.data.ListDataSet
 

L

Layer - Interface in org.cognity.neural.layer
A layer represents a set of neurons which share the same properties.
LayerInitializer - Interface in org.cognity.neural.init
The interface for layer initializator.
Linear - Class in org.cognity.math.functions
The linear function implementation.
Linear() - Constructor for class org.cognity.math.functions.Linear
 
Linear(double) - Constructor for class org.cognity.math.functions.Linear
 
Link - Interface in org.cognity.neural.link
A link is a directed connection between two layers.
ListDataSet - Class in org.cognity.data
Implements a data set which stores all data examples in a list.
ListDataSet(int, int) - Constructor for class org.cognity.data.ListDataSet
 
ListDataSet(int) - Constructor for class org.cognity.data.ListDataSet
 

M

MathUtil - Class in org.cognity.util
Helper math functions.
MatlabExporter - Class in org.cognity.data.io
This class allows you to export data sets into Matlab files.
MatlabExporter(String) - Constructor for class org.cognity.data.io.MatlabExporter
Creates a new exporter.
MatlabExporter(File) - Constructor for class org.cognity.data.io.MatlabExporter
Creates a new exporter.
MatlabImporter - Class in org.cognity.data.io
This class allows you to import data sets from Matlab files.
MatlabImporter(File) - Constructor for class org.cognity.data.io.MatlabImporter
Creates a new importer using the specified file.
MatlabImporter(File, String) - Constructor for class org.cognity.data.io.MatlabImporter
Creates a new importer using the specified file and input matrix name.
MatlabImporter(File, String, String) - Constructor for class org.cognity.data.io.MatlabImporter
Creates a new importer using the specified file and names of the matrices.
MaxErrorCondition - Class in org.cognity.neural.train
The stop condition for a gradient descent algorithm.
MaxErrorCondition(GradientDescent, double) - Constructor for class org.cognity.neural.train.MaxErrorCondition
Creates a new stop condition.
MaxErrorCondition(GradientDescent) - Constructor for class org.cognity.neural.train.MaxErrorCondition
Creates a new stop condition using default value for the maximum acceptable error.
MaxIterationCondition - Class in org.cognity.neural.train
The stop condition for an iterative process.
MaxIterationCondition(IterativeProcess) - Constructor for class org.cognity.neural.train.MaxIterationCondition
Creates a new stop condition using default value for the maximum iteration.
MaxIterationCondition(IterativeProcess, int) - Constructor for class org.cognity.neural.train.MaxIterationCondition
Creates a new stop condition.
MinErrorChangeCondition - Class in org.cognity.neural.train
The stop condition for a gradient descent algorithm.
MinErrorChangeCondition(GradientDescent, double) - Constructor for class org.cognity.neural.train.MinErrorChangeCondition
Creates a new stop condition.
MinErrorChangeCondition(GradientDescent) - Constructor for class org.cognity.neural.train.MinErrorChangeCondition
Creates a new stop condition using default minimal error change value.
mlp() - Static method in class org.cognity.neural.net.NeuralNetFactory
Returns a builder for a multilayer perceptron.
MlpNet - Class in org.cognity.neural.net
The implementation of a multilayer perceptron.
MlpNet.Builder - Class in org.cognity.neural.net
A builder for a multilayer perceptron.
MlpNet.Builder() - Constructor for class org.cognity.neural.net.MlpNet.Builder
Creates a new instance of the builder.

N

NeuralNet - Interface in org.cognity.neural.net
The basic interface for a neural network.
NeuralNetBuilder<E extends NeuralNet> - Interface in org.cognity.neural.net
Interface for a neural network builder.
NeuralNetFactory - Class in org.cognity.neural.net
The factory for all default types of neural networks.
NeuralNetInitializer - Interface in org.cognity.neural.init
Initializer's job is to randomize network's parameters i.e. weights and biases.
NeuralNetIO - Class in org.cognity.neural.io
A convenience class for reading/writing a neural network to a file.
NeuralNetIO() - Constructor for class org.cognity.neural.io.NeuralNetIO
 

O

OrCondition - Class in org.cognity.neural.train
The OR condition is made up from one or more other conditions.
OrCondition(List<StopCondition>) - Constructor for class org.cognity.neural.train.OrCondition
Creates an OR condition from specified conditions.
OrCondition(StopCondition...) - Constructor for class org.cognity.neural.train.OrCondition
Creates an OR condition from specified conditions.
org.cognity.data - package org.cognity.data
 
org.cognity.data.io - package org.cognity.data.io
 
org.cognity.math.functions - package org.cognity.math.functions
 
org.cognity.neural.init - package org.cognity.neural.init
 
org.cognity.neural.io - package org.cognity.neural.io
 
org.cognity.neural.layer - package org.cognity.neural.layer
 
org.cognity.neural.link - package org.cognity.neural.link
 
org.cognity.neural.net - package org.cognity.neural.net
 
org.cognity.neural.train - package org.cognity.neural.train
 
org.cognity.util - package org.cognity.util
 

P

ParametrizedFunction - Interface in org.cognity.math.functions
A function parametrized by some real number.

R

read(String) - Static method in class org.cognity.neural.io.NeuralNetIO
 
read(File) - Static method in class org.cognity.neural.io.NeuralNetIO
 
remove(Object) - Method in class org.cognity.data.ListDataSet
 
removeAll(Collection<?>) - Method in class org.cognity.data.ListDataSet
 
retainAll(Collection<?>) - Method in class org.cognity.data.ListDataSet
 

S

setBias(int, double) - Method in class org.cognity.neural.layer.GenericTransferLayer
 
setBias(int, double) - Method in interface org.cognity.neural.layer.TransferLayer
Sets the bias value for the specified neuron.
setCurrentError(double) - Method in class org.cognity.neural.train.GradientDescent
Sets the current error value.
setInputMatrixName(String) - Method in class org.cognity.data.io.AbstractMatlabIO
Sets the name for the input matrix.
setInputSize(int) - Method in class org.cognity.neural.net.MlpNet.Builder
Sets the number of inputs for a network.
setLearningRate(double) - Method in class org.cognity.neural.train.GradientDescent
Sets the learning rate value.
setMomentum(double) - Method in class org.cognity.neural.train.GradientDescent
Sets the momentum value.
setOrientation(AbstractMatlabIO.Orientation) - Method in class org.cognity.data.io.AbstractMatlabIO
Sets the orientation of the data vectors in the matrix.
setParam(double) - Method in class org.cognity.math.functions.FastGaussian
Sets the sigma parameter.
setParam(double) - Method in class org.cognity.math.functions.FastSigmoid
Sets the beta parameter.
setParam(double) - Method in class org.cognity.math.functions.Gaussian
Sets the sigma parameter.
setParam(double) - Method in class org.cognity.math.functions.Linear
 
setParam(double) - Method in interface org.cognity.math.functions.ParametrizedFunction
Sets the parameter of this function.
setParam(double) - Method in class org.cognity.math.functions.Sigmoid
 
setStopCondition(StopCondition) - Method in class org.cognity.neural.train.GradientDescent
 
setStopCondition(StopCondition) - Method in interface org.cognity.neural.train.IterativeProcess
Sets a stop condition for this process.
setTargetMatrixName(String) - Method in class org.cognity.data.io.AbstractMatlabIO
Sets the name for the target matrix.
setTransferFunc(Function) - Method in class org.cognity.neural.layer.GenericTransferLayer
 
setTransferFunc(Function) - Method in interface org.cognity.neural.layer.TransferLayer
Sets the transfer function for this layer.
setWeight(int, int, double) - Method in interface org.cognity.neural.link.Link
Sets a weight between toNeuron-th neuron in the target layer and fromNeuron-th neuron in the source layer.
setWeight(int, int, double) - Method in class org.cognity.neural.link.WeightedLink
 
Sigmoid - Class in org.cognity.math.functions
Implements a sigmoid function defined as follows:
$f(x) = \frac{1}{1+e^{-\beta \cdot x}}$
Where $\beta$ is a constant defined by user.
Sigmoid() - Constructor for class org.cognity.math.functions.Sigmoid
 
Sigmoid(double) - Constructor for class org.cognity.math.functions.Sigmoid
 
size() - Method in class org.cognity.data.ListDataSet
 
stimulate(int, double) - Method in class org.cognity.neural.layer.GenericTransferLayer
Stimulates specified neuron with the given value.
stimulate(int, double) - Method in class org.cognity.neural.layer.InputLayer
Sets input and output of specified neuron to the given value.
stimulate(int, double) - Method in interface org.cognity.neural.layer.Layer
Stimulates specified neuron with given value.
StopCondition - Interface in org.cognity.neural.train
The stop condition for an iterative process.

T

Tanh - Class in org.cognity.math.functions
Implements the hyperbolic tangent.
Tanh() - Constructor for class org.cognity.math.functions.Tanh
 
toArray() - Method in class org.cognity.data.ListDataSet
 
toArray(T[]) - Method in class org.cognity.data.ListDataSet
 
toString() - Method in class org.cognity.math.functions.BipolarStep
 
toString() - Method in class org.cognity.math.functions.FastGaussian
 
toString() - Method in class org.cognity.math.functions.FastSigmoid
 
toString() - Method in class org.cognity.math.functions.FastTanh
 
toString() - Method in class org.cognity.math.functions.Gaussian
 
toString() - Method in class org.cognity.math.functions.Identity
 
toString() - Method in class org.cognity.math.functions.Linear
 
toString() - Method in class org.cognity.math.functions.Sigmoid
 
toString() - Method in class org.cognity.math.functions.Tanh
 
toString() - Method in class org.cognity.neural.layer.GenericTransferLayer
 
toString() - Method in class org.cognity.neural.layer.InputLayer
 
toString() - Method in class org.cognity.neural.net.AbstractNeuralNet
 
toString() - Method in class org.cognity.neural.train.MaxErrorCondition
 
toString() - Method in class org.cognity.neural.train.MaxIterationCondition
 
toString() - Method in class org.cognity.neural.train.MinErrorChangeCondition
 
train(DataSet) - Method in class org.cognity.neural.train.GradientDescent
 
train(DataSet) - Method in interface org.cognity.neural.train.TrainingRule
Performs the training of a neural network.
trainExample(DataExample) - Method in class org.cognity.neural.train.Backpropagation
Learns a single pattern.
trainExample(DataExample) - Method in class org.cognity.neural.train.GradientDescent
Learn a single data example.
TrainingRule - Interface in org.cognity.neural.train
The basic interface for a training rule.
TransferLayer - Interface in org.cognity.neural.layer
The transfer layer is a basic model of a layer, that processes data in a neural network.

U

UniformInitializer - Class in org.cognity.neural.init
The uniform initializer sets every weight and bias to a random number from range [min, max).
UniformInitializer() - Constructor for class org.cognity.neural.init.UniformInitializer
 
UniformInitializer(double, double) - Constructor for class org.cognity.neural.init.UniformInitializer
Creates a new initializer using specified range.

V

valueOf(String) - Static method in enum org.cognity.data.io.AbstractMatlabIO.Orientation
Returns the enum constant of this type with the specified name.
values() - Static method in enum org.cognity.data.io.AbstractMatlabIO.Orientation
Returns an array containing the constants of this enum type, in the order they are declared.

W

WeightedLink - Class in org.cognity.neural.link
The weighted link is most widely used type of a link.
WeightedLink(Layer, Layer) - Constructor for class org.cognity.neural.link.WeightedLink
Creates a link using specified layers.
write(String, NeuralNet) - Static method in class org.cognity.neural.io.NeuralNetIO
 
write(File, NeuralNet) - Static method in class org.cognity.neural.io.NeuralNetIO
 
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