Index (cognity 0.1.0 API)

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:

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

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