Index (Artificial neural networks 4.0-SNAPSHOT API)

A C D E F G I K L M N O Q R S T U V
All Classes All Packages

A

addLink(Neuron, Neuron) - Method in class org.apache.commons.math4.neuralnet.Network: Adds a link from neuron a to neuron b.
applyAsDouble(double[], double[]) - Method in class org.apache.commons.math4.neuralnet.EuclideanDistance
applyAsDouble(long) - Method in class org.apache.commons.math4.neuralnet.sofm.util.ExponentialDecayFunction: Computes a e^{-numCall / b}.
applyAsDouble(long) - Method in class org.apache.commons.math4.neuralnet.sofm.util.QuasiSigmoidDecayFunction: Computes the value of the learning factor.

C

CENTER - org.apache.commons.math4.neuralnet.twod.NeuronSquareMesh2D.HorizontalDirection: Current column.
CENTER - org.apache.commons.math4.neuralnet.twod.NeuronSquareMesh2D.VerticalDirection: Current row.
compareAndSetFeatures(double[], double[]) - Method in class org.apache.commons.math4.neuralnet.Neuron: Tries to atomically update the neuron's features.
computeImage(NeuronSquareMesh2D) - Method in interface org.apache.commons.math4.neuralnet.twod.util.MapVisualization: Creates an image of the map.
computeImage(NeuronSquareMesh2D) - Method in class org.apache.commons.math4.neuralnet.twod.util.UnifiedDistanceMatrix: Computes the distances between a unit of the map and its neighbours.
computeImage(NeuronSquareMesh2D, Iterable<double[]>) - Method in interface org.apache.commons.math4.neuralnet.twod.util.MapDataVisualization: Creates an image of the data metrics when represented by the map.
computeImage(NeuronSquareMesh2D, Iterable<double[]>) - Method in class org.apache.commons.math4.neuralnet.twod.util.SmoothedDataHistogram: Creates an image of the data metrics when represented by the map.
computeQualityIndicators(Iterable<double[]>) - Method in class org.apache.commons.math4.neuralnet.twod.NeuronSquareMesh2D: Computes various indicators of the quality of the representation of the given data by this map.
computeQuantizationError(Iterable<double[]>, Iterable<Neuron>, DistanceMeasure) - Static method in class org.apache.commons.math4.neuralnet.MapUtils: Computes the quantization error.
computeTopographicError(Iterable<double[]>, Network, DistanceMeasure) - Static method in class org.apache.commons.math4.neuralnet.MapUtils: Computes the topographic error.
copy() - Method in class org.apache.commons.math4.neuralnet.Network: Performs a deep copy of this instance.
copy() - Method in class org.apache.commons.math4.neuralnet.Neuron: Performs a deep copy of this instance.
copy() - Method in class org.apache.commons.math4.neuralnet.twod.NeuronSquareMesh2D: Performs a deep copy of this instance.
createNeuron(double[]) - Method in class org.apache.commons.math4.neuralnet.Network: Creates a neuron and assigns it a unique identifier.

D

deleteLink(Neuron, Neuron) - Method in class org.apache.commons.math4.neuralnet.Network: Deletes the link between neurons a and b.
deleteNeuron(Neuron) - Method in class org.apache.commons.math4.neuralnet.Network: Deletes a neuron.
DistanceMeasure - Interface in org.apache.commons.math4.neuralnet: Interface for distance measures between two n-dimensional vectors.
DOWN - org.apache.commons.math4.neuralnet.twod.NeuronSquareMesh2D.VerticalDirection: Row below the current row.

E

EuclideanDistance - Class in org.apache.commons.math4.neuralnet: Euclidean distance measures of n-dimensional vectors.
EuclideanDistance() - Constructor for class org.apache.commons.math4.neuralnet.EuclideanDistance
exponentialDecay(double, double, long) - Static method in class org.apache.commons.math4.neuralnet.sofm.LearningFactorFunctionFactory: Creates an exponential decay function.
exponentialDecay(double, double, long) - Static method in class org.apache.commons.math4.neuralnet.sofm.NeighbourhoodSizeFunctionFactory: Creates an exponential decay function.
ExponentialDecayFunction - Class in org.apache.commons.math4.neuralnet.sofm.util: Exponential decay function: a e^{-x / b}, where x is the (integer) independent variable.
ExponentialDecayFunction(double, double, long) - Constructor for class org.apache.commons.math4.neuralnet.sofm.util.ExponentialDecayFunction: Creates an instance.

F

FeatureInitializer - Interface in org.apache.commons.math4.neuralnet: Defines how to assign the first value of a neuron's feature.
FeatureInitializerFactory - Class in org.apache.commons.math4.neuralnet: Creates functions that will select the initial values of a neuron's features.
from(int, long[], double[][], long[][]) - Static method in class org.apache.commons.math4.neuralnet.Network: Builds a network from a list of neurons and their neighbours.
function(DoubleUnaryOperator, double, double) - Static method in class org.apache.commons.math4.neuralnet.FeatureInitializerFactory: Creates an initializer from a univariate function f(x).

G

getColumn() - Method in class org.apache.commons.math4.neuralnet.twod.util.LocationFinder.Location
getFeatures() - Method in class org.apache.commons.math4.neuralnet.Neuron: Gets the neuron's features.
getFeatures(int) - Method in class org.apache.commons.math4.neuralnet.oned.NeuronString: Retrieves the features set from the neuron at location i in the map.
getFeaturesSize() - Method in class org.apache.commons.math4.neuralnet.Network: Gets the size of the neurons' features set.
getIdentifier() - Method in class org.apache.commons.math4.neuralnet.Neuron: Gets the neuron's identifier.
getLocation(Neuron) - Method in class org.apache.commons.math4.neuralnet.twod.util.LocationFinder: Retrieves a neuron's grid coordinates.
getMeanQuantizationError() - Method in class org.apache.commons.math4.neuralnet.twod.NeuronSquareMesh2D.DataVisualization
getMeanTopographicError() - Method in class org.apache.commons.math4.neuralnet.twod.NeuronSquareMesh2D.DataVisualization
getNeighbours(Iterable<Neuron>) - Method in class org.apache.commons.math4.neuralnet.Network: Retrieves the neurons in the neighbourhood of any neuron in the neurons list.
getNeighbours(Iterable<Neuron>, Iterable<Neuron>) - Method in class org.apache.commons.math4.neuralnet.Network: Retrieves the neurons in the neighbourhood of any neuron in the neurons list.
getNeighbours(Neuron) - Method in class org.apache.commons.math4.neuralnet.Network: Retrieves the neighbours of the given neuron.
getNeighbours(Neuron, Iterable<Neuron>) - Method in class org.apache.commons.math4.neuralnet.Network: Retrieves the neighbours of the given neuron.
getNetwork() - Method in class org.apache.commons.math4.neuralnet.oned.NeuronString: Retrieves the underlying network.
getNetwork() - Method in class org.apache.commons.math4.neuralnet.twod.NeuronSquareMesh2D: Retrieves the underlying network.
getNeuron(int, int) - Method in class org.apache.commons.math4.neuralnet.twod.NeuronSquareMesh2D: Retrieves the neuron at location (i, j) in the map.
getNeuron(int, int, NeuronSquareMesh2D.HorizontalDirection, NeuronSquareMesh2D.VerticalDirection) - Method in class org.apache.commons.math4.neuralnet.twod.NeuronSquareMesh2D: Retrieves the requested neuron relative to the given (row, col) position.
getNeuron(long) - Method in class org.apache.commons.math4.neuralnet.Network: Retrieves the neuron with the given (unique) id.
getNeurons() - Method in class org.apache.commons.math4.neuralnet.Network
getNormalizedHits() - Method in class org.apache.commons.math4.neuralnet.twod.NeuronSquareMesh2D.DataVisualization
getNumberOfAttemptedUpdates() - Method in class org.apache.commons.math4.neuralnet.Neuron: Retrieves the number of calls to the compareAndSetFeatures method.
getNumberOfCalls() - Method in class org.apache.commons.math4.neuralnet.sofm.KohonenUpdateAction: Retrieves the number of calls to the update method.
getNumberOfColumns() - Method in class org.apache.commons.math4.neuralnet.twod.NeuronSquareMesh2D: Gets the number of neurons in each column of this map.
getNumberOfRows() - Method in class org.apache.commons.math4.neuralnet.twod.NeuronSquareMesh2D: Gets the number of neurons in each row of this map.
getNumberOfSamples() - Method in class org.apache.commons.math4.neuralnet.twod.NeuronSquareMesh2D.DataVisualization
getNumberOfSuccessfulUpdates() - Method in class org.apache.commons.math4.neuralnet.Neuron: Retrieves the number of successful calls to the compareAndSetFeatures method.
getQuantizationError() - Method in class org.apache.commons.math4.neuralnet.twod.NeuronSquareMesh2D.DataVisualization
getRow() - Method in class org.apache.commons.math4.neuralnet.twod.util.LocationFinder.Location
getSize() - Method in class org.apache.commons.math4.neuralnet.Neuron: Gets the length of the feature set.
getSize() - Method in class org.apache.commons.math4.neuralnet.oned.NeuronString: Gets the number of neurons.
getSquareNeighbourhood() - Method in class org.apache.commons.math4.neuralnet.twod.NeuronSquareMesh2D: Indicates the type of connectivity between neurons.
getTopographicError() - Method in class org.apache.commons.math4.neuralnet.twod.NeuronSquareMesh2D.DataVisualization
getUMatrix() - Method in class org.apache.commons.math4.neuralnet.twod.NeuronSquareMesh2D.DataVisualization

I

ID_IN_USE - Static variable in exception org.apache.commons.math4.neuralnet.internal.NeuralNetException: Error message for "identifier already used" condition.
ID_NOT_FOUND - Static variable in exception org.apache.commons.math4.neuralnet.internal.NeuralNetException: Error message for "identifier not found" condition.
isWrapped() - Method in class org.apache.commons.math4.neuralnet.oned.NeuronString: Indicates whether the line of neurons is wrapped.
isWrappedColumn() - Method in class org.apache.commons.math4.neuralnet.twod.NeuronSquareMesh2D: Indicates whether the map is wrapped along the second dimension.
isWrappedRow() - Method in class org.apache.commons.math4.neuralnet.twod.NeuronSquareMesh2D: Indicates whether the map is wrapped along the first dimension.
iterator() - Method in class org.apache.commons.math4.neuralnet.Network
iterator() - Method in class org.apache.commons.math4.neuralnet.twod.NeuronSquareMesh2D

K

KohonenTrainingTask - Class in org.apache.commons.math4.neuralnet.sofm: Trainer for Kohonen's Self-Organizing Map.
KohonenTrainingTask(Network, Iterator<double[]>, KohonenUpdateAction) - Constructor for class org.apache.commons.math4.neuralnet.sofm.KohonenTrainingTask: Creates a (sequential) trainer for the given network.
KohonenUpdateAction - Class in org.apache.commons.math4.neuralnet.sofm: Update formula for Kohonen's Self-Organizing Map.
KohonenUpdateAction(DistanceMeasure, LearningFactorFunction, NeighbourhoodSizeFunction) - Constructor for class org.apache.commons.math4.neuralnet.sofm.KohonenUpdateAction

L

LearningFactorFunction - Interface in org.apache.commons.math4.neuralnet.sofm: Provides the learning rate as a function of the number of calls already performed during the learning task.
LearningFactorFunctionFactory - Class in org.apache.commons.math4.neuralnet.sofm: Factory for creating instances of LearningFactorFunction.
LEFT - org.apache.commons.math4.neuralnet.twod.NeuronSquareMesh2D.HorizontalDirection: Column at the left of the current column.
Location(int, int) - Constructor for class org.apache.commons.math4.neuralnet.twod.util.LocationFinder.Location
LocationFinder - Class in org.apache.commons.math4.neuralnet.twod.util: Helper class to find the grid coordinates of a neuron.
LocationFinder(NeuronSquareMesh2D) - Constructor for class org.apache.commons.math4.neuralnet.twod.util.LocationFinder: Builds a finder to retrieve the locations of neurons that belong to the given map.
LocationFinder.Location - Class in org.apache.commons.math4.neuralnet.twod.util: Container holding a (row, column) pair.

M

MapDataVisualization - Interface in org.apache.commons.math4.neuralnet.twod.util: Interface for algorithms that compute some metrics of the projection of data on a 2D-map.
MapRanking - Class in org.apache.commons.math4.neuralnet: Utility for ranking the units (neurons) of a network.
MapRanking(Iterable<Neuron>, DistanceMeasure) - Constructor for class org.apache.commons.math4.neuralnet.MapRanking
MapUtils - Class in org.apache.commons.math4.neuralnet: Utilities for network maps.
MapVisualization - Interface in org.apache.commons.math4.neuralnet.twod.util: Interface for algorithms that compute some property of a 2D-map.
MOORE - org.apache.commons.math4.neuralnet.SquareNeighbourhood: Moore neighbourhood: in two dimensions, each (internal) neuron has eight neighbours.

N

NeighbourhoodSizeFunction - Interface in org.apache.commons.math4.neuralnet.sofm: Provides the network neighbourhood's size as a function of the number of calls already performed during the learning task.
NeighbourhoodSizeFunctionFactory - Class in org.apache.commons.math4.neuralnet.sofm: Factory for creating instances of NeighbourhoodSizeFunction.
Network - Class in org.apache.commons.math4.neuralnet: Neural network, composed of Neuron instances and the links between them.
Network(long, int) - Constructor for class org.apache.commons.math4.neuralnet.Network
NeuralNetException - Exception in org.apache.commons.math4.neuralnet.internal: Exception class with constants for frequently used messages.
NeuralNetException(String, Object...) - Constructor for exception org.apache.commons.math4.neuralnet.internal.NeuralNetException: Create an exception where the message is constructed by applying the format() method from java.text.MessageFormat.
Neuron - Class in org.apache.commons.math4.neuralnet: Describes a neuron element of a neural network.
NeuronSquareMesh2D - Class in org.apache.commons.math4.neuralnet.twod: Neural network with the topology of a two-dimensional surface.
NeuronSquareMesh2D(boolean, boolean, SquareNeighbourhood, double[][][]) - Constructor for class org.apache.commons.math4.neuralnet.twod.NeuronSquareMesh2D
NeuronSquareMesh2D(int, boolean, int, boolean, SquareNeighbourhood, FeatureInitializer[]) - Constructor for class org.apache.commons.math4.neuralnet.twod.NeuronSquareMesh2D: Creates a two-dimensional network composed of square cells: Each neuron not located on the border of the mesh has four neurons linked to it.
NeuronSquareMesh2D.DataVisualization - Class in org.apache.commons.math4.neuralnet.twod: Miscellaneous indicators of the map quality.
NeuronSquareMesh2D.HorizontalDirection - Enum in org.apache.commons.math4.neuralnet.twod: Horizontal (along row) direction.
NeuronSquareMesh2D.VerticalDirection - Enum in org.apache.commons.math4.neuralnet.twod: Vertical (along column) direction.
NeuronString - Class in org.apache.commons.math4.neuralnet.oned: Neural network with the topology of a one-dimensional line.
NeuronString(int, boolean, FeatureInitializer[]) - Constructor for class org.apache.commons.math4.neuralnet.oned.NeuronString: Creates a one-dimensional network: Each neuron not located on the border of the mesh has two neurons linked to it.
NO_DATA - Static variable in exception org.apache.commons.math4.neuralnet.internal.NeuralNetException: Error message for "out of range" condition.
NOT_STRICTLY_POSITIVE - Static variable in exception org.apache.commons.math4.neuralnet.internal.NeuralNetException: Error message for "not strictly positive" condition.

O

org.apache.commons.math4.neuralnet - package org.apache.commons.math4.neuralnet: Neural networks.
org.apache.commons.math4.neuralnet.internal - package org.apache.commons.math4.neuralnet.internal: Internal utility classes.
org.apache.commons.math4.neuralnet.oned - package org.apache.commons.math4.neuralnet.oned: One-dimensional neural networks.
org.apache.commons.math4.neuralnet.sofm - package org.apache.commons.math4.neuralnet.sofm: Self Organizing Feature Map.
org.apache.commons.math4.neuralnet.sofm.util - package org.apache.commons.math4.neuralnet.sofm.util: Miscellaneous utilities.
org.apache.commons.math4.neuralnet.twod - package org.apache.commons.math4.neuralnet.twod: Two-dimensional neural networks.
org.apache.commons.math4.neuralnet.twod.util - package org.apache.commons.math4.neuralnet.twod.util: Utilities to visualize two-dimensional neural networks.
OUT_OF_RANGE - Static variable in exception org.apache.commons.math4.neuralnet.internal.NeuralNetException: Error message for "out of range" condition.

Q

quasiSigmoidDecay(double, double, long) - Static method in class org.apache.commons.math4.neuralnet.sofm.LearningFactorFunctionFactory: Creates an sigmoid-like LearningFactorFunction function.
quasiSigmoidDecay(double, double, long) - Static method in class org.apache.commons.math4.neuralnet.sofm.NeighbourhoodSizeFunctionFactory: Creates an sigmoid-like NeighbourhoodSizeFunction function.
QuasiSigmoidDecayFunction - Class in org.apache.commons.math4.neuralnet.sofm.util: Decay function whose shape is similar to a sigmoid.
QuasiSigmoidDecayFunction(double, double, long) - Constructor for class org.apache.commons.math4.neuralnet.sofm.util.QuasiSigmoidDecayFunction: Creates an instance.

R

randomize(ContinuousUniformSampler, FeatureInitializer) - Static method in class org.apache.commons.math4.neuralnet.FeatureInitializerFactory: Adds some amount of random data to the given initializer.
rank(double[]) - Method in class org.apache.commons.math4.neuralnet.MapRanking: Creates a list of the neurons whose features best correspond to the given features.
rank(double[], int) - Method in class org.apache.commons.math4.neuralnet.MapRanking: Creates a list of the neurons whose features best correspond to the given features.
RIGHT - org.apache.commons.math4.neuralnet.twod.NeuronSquareMesh2D.HorizontalDirection: Column at the right of the current column.
run() - Method in class org.apache.commons.math4.neuralnet.sofm.KohonenTrainingTask

S

SIZE_MISMATCH - Static variable in exception org.apache.commons.math4.neuralnet.internal.NeuralNetException: Error message for "size mismatch" condition.
SmoothedDataHistogram - Class in org.apache.commons.math4.neuralnet.twod.util: Visualization of high-dimensional data projection on a 2D-map.
SmoothedDataHistogram(int, DistanceMeasure) - Constructor for class org.apache.commons.math4.neuralnet.twod.util.SmoothedDataHistogram
SquareNeighbourhood - Enum in org.apache.commons.math4.neuralnet: Defines neighbourhood types.

T

TOO_LARGE - Static variable in exception org.apache.commons.math4.neuralnet.internal.NeuralNetException: Error message for "too large" condition.
TOO_SMALL - Static variable in exception org.apache.commons.math4.neuralnet.internal.NeuralNetException: Error message for "too small" condition.

U

UnifiedDistanceMatrix - Class in org.apache.commons.math4.neuralnet.twod.util: U-Matrix visualization of high-dimensional data projection.
UnifiedDistanceMatrix(DistanceMeasure) - Constructor for class org.apache.commons.math4.neuralnet.twod.util.UnifiedDistanceMatrix
uniform(UniformRandomProvider, double, double) - Static method in class org.apache.commons.math4.neuralnet.FeatureInitializerFactory: Uniform sampling of the given range.
UP - org.apache.commons.math4.neuralnet.twod.NeuronSquareMesh2D.VerticalDirection: Row above the current row.
update(Network, double[]) - Method in class org.apache.commons.math4.neuralnet.sofm.KohonenUpdateAction: Updates the network in response to the sample features.
update(Network, double[]) - Method in interface org.apache.commons.math4.neuralnet.UpdateAction: Updates the network in response to the sample features.
UpdateAction - Interface in org.apache.commons.math4.neuralnet: Describes how to update the network in response to a training sample.

V

value() - Method in interface org.apache.commons.math4.neuralnet.FeatureInitializer: Selects the initial value.
value(long) - Method in interface org.apache.commons.math4.neuralnet.sofm.LearningFactorFunction: Computes the learning rate at the current call.
value(long) - Method in interface org.apache.commons.math4.neuralnet.sofm.NeighbourhoodSizeFunction: Computes the neighbourhood size at the current call.
valueOf(String) - Static method in enum org.apache.commons.math4.neuralnet.SquareNeighbourhood: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.commons.math4.neuralnet.twod.NeuronSquareMesh2D.HorizontalDirection: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.commons.math4.neuralnet.twod.NeuronSquareMesh2D.VerticalDirection: Returns the enum constant of this type with the specified name.
values() - Static method in enum org.apache.commons.math4.neuralnet.SquareNeighbourhood: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.commons.math4.neuralnet.twod.NeuronSquareMesh2D.HorizontalDirection: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.commons.math4.neuralnet.twod.NeuronSquareMesh2D.VerticalDirection: Returns an array containing the constants of this enum type, in the order they are declared.
VON_NEUMANN - org.apache.commons.math4.neuralnet.SquareNeighbourhood: Von Neumann neighbourhood: in two dimensions, each (internal) neuron has four neighbours.

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