- calcFitness() - Method in class netevo.NetPhenotype
-
Calculates the fitness of this phenotype instance.
- chromosome - Variable in class netevo.decoders.Decoder
-
The chromosome to decode.
- chromosomeNumber - Variable in class netevo.decoders.Decoder
-
The chromosome index.
- Classification - Class in netevo.fitness
-
Classification accuracy based on winner-takes-all evaluation of network output.
- Classification(PatternSet) - Constructor for class netevo.fitness.Classification
-
Constructs the fitness function with a test set.
- clearFunctionPool() - Method in class netevo.features.Functions
-
Removes all activation functions from the pool.
- clone() - Method in class netevo.decoders.Decoder
-
Return a shallow clone.
- clone() - Method in class netevo.misc.Matrix
-
A deep clone.
- clone() - Method in class netevo.misc.NetMatrix
-
A deep clone.
- clone() - Method in class netevo.misc.SpikeMatrix
-
A deep clone.
- clone() - Method in class netevo.NetPhenotype
-
Returns a shallow clone.
- cloneLink(Link, Neuron, Neuron, double) - Static method in class netevo.misc.Utilities
-
Clones a given link and connects it with the given
parameters.
- close() - Method in class netevo.misc.EvoGenStats
-
Close the stats file.
- compareTo(Feature) - Method in class netevo.features.Feature
-
The natural ordering based on IDs is used for the order of decoding features.
- compute(NeuralNet) - Method in class netevo.fitness.FitnessFunction
-
Computes the complete fitness with potential regularization.
- createLinks(NeuralNet) - Method in class netevo.NetEvolver
-
Adds the links to the generated network.
- createLinks(NeuralNet) - Method in class netevo.SpikingNetEvolver
-
Creates the spiking links with their spiking parameters.
- createNet(NeuralNet) - Method in class netevo.NetEvolver
-
Creates a network based on the net matrix.
- createNeurons(NeuralNet) - Method in class netevo.NetEvolver
-
Adds the neurons defined in matrix to net, which is built in createNet().
- createNeurons(NeuralNet) - Method in class netevo.SpikingNetEvolver
-
Creates the spiking neurons with their spiking parameters.
- Decoder - Class in netevo.decoders
-
Interpret a JEvolution Chromosome, calculate feature lengths,
and read bits, integers and real numbers.
- Decoder() - Constructor for class netevo.decoders.Decoder
-
Constructs the Decoder.
- decoder - Variable in class netevo.features.Feature
-
The decoder for this Feature.
- Delays - Class in netevo.features
-
Feature for the evolution of SNN link delays [ms].
- Delays(Decoder) - Constructor for class netevo.features.Delays
-
Constructs the feature with default min = 0.0, max = 10.0.
- DELAYS - Static variable in class netevo.features.Feature
-
- develop(List<Chromosome>) - Method in class netevo.Evolver
-
Develops the given list of chromosomes into a neural network and training infrastructure depending on
the features to be evolved.
- develop() - Method in class netevo.features.AbsRefPeriods
-
Develops the feature.
- develop() - Method in class netevo.features.Bias
-
Develops the feature.
- develop() - Method in class netevo.features.BPTraining
-
Develops the feature fields.
- develop() - Method in class netevo.features.Delays
-
Develops the feature.
- develop() - Method in class netevo.features.Feature
-
Develops the feature.
- develop() - Method in class netevo.features.Functions
-
Collects the functions from the pool and puts it into a list according to the neuron order.
- develop() - Method in class netevo.features.IntValue
-
Develops the feature.
- develop() - Method in class netevo.features.Links
-
Develops the feature.
- develop() - Method in class netevo.features.Neurons
-
Develops the feature.
- develop() - Method in class netevo.features.Patterns
-
Develops the feature.
- develop() - Method in class netevo.features.RealValues
-
Develops the feature by decoding all real values.
- develop() - Method in class netevo.features.RelRefPeriods
-
Develops the feature.
- develop() - Method in class netevo.features.RpropTraining
-
Develops the feature fields.
- develop() - Method in class netevo.features.Thresholds
-
Develops the feature.
- develop() - Method in class netevo.features.Weights
-
Develops the feature.
- develop() - Method in class netevo.NetEvolver
-
Creates the evolved net from the net matrix.
- develop() - Method in class netevo.SpikingNetEvolver
-
Creates the evolved net from the net matrix.
- develop(NeuralNet) - Method in class netevo.TrainEvolver
-
Trains the given network with the already developed infrastructure.
- doInputs(boolean) - Method in class netevo.features.Functions
-
Sets status of input neuron AFs.
- doOntogeny(List<Chromosome>) - Method in class netevo.NetPhenotype
-
Maps the genotype to a phenotype network.
- doOutputs(boolean) - Method in class netevo.features.Functions
-
Sets status of output neuron AFs.
- doStatistics(Population) - Method in class netevo.misc.NetReporter
-
Does population statistics, records the best individual of the run.
- doStatistics() - Method in class netevo.misc.NetReporter
-
Does stats after end of run.
- geneLength - Variable in class netevo.decoders.Decoder
-
Length of the gene on the chromosome.
- geneStart - Variable in class netevo.decoders.Decoder
-
The start index of a gene on the chromosome.
- getAbsRefPeriod(int) - Method in class netevo.misc.SpikeMatrix
-
Returns an absolute refractory period value.
- getBestIndividual() - Method in class netevo.misc.NetReporter
-
Returns the best individual of the current run so far.
- getBias(int) - Method in class netevo.misc.NetMatrix
-
Returns a bias value.
- getBiasCount() - Method in class netevo.misc.NetMatrix
-
Returns the number of biases encoded in the matrix.
- getBiasCount() - Method in class netevo.NetEvolver
-
Returns the number of bias values to be evolved.
- getChromosome() - Method in class netevo.decoders.Decoder
-
Returns the chromosome, for which the decoder is responsible.
- getChromosomeNumber() - Method in class netevo.decoders.Decoder
-
Returns the chromosome number for this decoder.
- getClassName(Object) - Static method in class netevo.misc.Utilities
-
Returns the unqualified class name, i.e., with all package names dropped.
- getDecoder() - Method in class netevo.features.Feature
-
Return the decoder used by this feature.
- getDigits(int, int) - Static method in class netevo.misc.Utilities
-
Calculate the minimal number of digits needed to represent the value in the given
number base.
- getField(int) - Method in class netevo.features.Feature
-
Returns a specific field of a sub-feature.
- getFitness(NeuralNet) - Method in class netevo.fitness.Classification
-
Returns the classification accuracy in [0, 1] using Boone's NetError class
for calculating the classification error.
- getFitness(NeuralNet) - Method in class netevo.fitness.FitnessFunction
-
Computes a fitness of the given network.
- getFitness(NeuralNet) - Method in class netevo.fitness.NetError
-
Returns the network fitness according to 1 / (1 + netError).
- getFitness() - Method in class netevo.NetPhenotype
-
Returns the fitness of this phenotype instance.
- getFitnessFunction() - Method in class netevo.Evolver
-
Returns the fitness function.
- getFunctionCount() - Method in class netevo.features.Functions
-
Returns the number of activation functions in the pool.
- getGeneLength() - Method in class netevo.decoders.Decoder
-
Returns the length (number of bases) of a gene on the chromosome.
- getGeneStart() - Method in class netevo.decoders.Decoder
-
Returns the start index of the gene on the chromosome.
- getHiddenCount() - Method in class netevo.NetEvolver
-
Returns the number of hidden neurons of the template.
- getId() - Method in class netevo.features.Feature
-
Returns the unique feature ID, which is used to assign a feature to the
corresponding evolver.
- getInputCount() - Method in class netevo.NetEvolver
-
Returns the number of input neurons of the template.
- getInputNeuronCount() - Method in class netevo.misc.NetMatrix
-
Returns the number of input neurons encoded with this matrix.
- getLinkCount() - Method in class netevo.misc.NetMatrix
-
Returns the number of links encoded in the matrix.
- getMaxValue() - Method in class netevo.features.Feature
-
Returns the maximal value to develop.
- getMinValue() - Method in class netevo.features.Feature
-
Returns the minimal value to develop.
- getNet() - Method in class netevo.NetEvolver
-
Returns the evolved network.
- getNet() - Method in class netevo.NetPhenotype
-
Returns the network represented by this phenotype.
- getNetEvolver() - Method in class netevo.Evolver
-
Returns the net evolver.
- getNeuronCount() - Method in class netevo.misc.NetMatrix
-
Returns the number of neurons encoded with this matrix.
- getNeuronCount() - Method in class netevo.NetEvolver
-
Returns the total number of neurons of the template.
- getOutputCount() - Method in class netevo.NetEvolver
-
Returns the number of output neurons of the template.
- getPatternCount() - Method in class netevo.TrainEvolver
-
Returns the number of patterns in the template set.
- getPrune(int) - Method in class netevo.misc.NetMatrix
-
Returns the prune status.
- getRegFactor() - Method in class netevo.fitness.FitnessFunction
-
Returns the regularization factor.
- getRelRefPeriod(int) - Method in class netevo.misc.SpikeMatrix
-
Returns a relative refractory period value.
- getThreshold(int) - Method in class netevo.misc.SpikeMatrix
-
Returns a threshold value.
- getTopologicalSort(NeuralNet) - Static method in class netevo.misc.Utilities
-
Returns a sorted list of all neurons of a network in the order input-hidden-output.
- getTrainer() - Method in class netevo.TrainEvolver
-
Returns the evolved trainer.
- getTrainEvolver() - Method in class netevo.Evolver
-
Returns the train evolver.
- getType(int) - Method in class netevo.misc.NetMatrix
-
Returns a neuron type.
- getValue() - Method in class netevo.features.IntValue
-
- getValue(NeuralNet) - Method in class netevo.fitness.RegularizationFactor
-
Returns the factor value for set type.
- getValue(int, int) - Method in class netevo.misc.Matrix
-
Returns a matrix element.
- getValueCount() - Method in class netevo.features.Feature
-
Returns the number of values for this feature.
- getValues() - Method in class netevo.features.RealValues
-
Returns the evolved real values.
- getWeight() - Method in class netevo.fitness.RegularizationFactor
-
Returns the weight of the factor.
- getWeightCount() - Method in class netevo.NetEvolver
-
Returns the number of weights (=links) to be evolved.
- id - Variable in class netevo.features.Feature
-
The unique feature ID.
- INPUT - Static variable in class netevo.misc.NetMatrix
-
An input neuron.
- IntDecoder - Class in netevo.decoders
-
Decoder for IntChromosomes.
- IntDecoder() - Constructor for class netevo.decoders.IntDecoder
-
Constructs the IntDecoder with a gene length of one.
- IntValue - Class in netevo.features
-
An arbitrary feature described by a single integer value.
- IntValue(Decoder, double, double) - Constructor for class netevo.features.IntValue
-
- invalidate(int, int) - Method in class netevo.misc.Matrix
-
Invalidates an element in the matrix.
- isAccelerate() - Method in class netevo.fitness.Classification
-
Returns the acceleration status.
- isInputs() - Method in class netevo.features.Functions
-
Returns status of input neuron AFs.
- isInputs() - Method in class netevo.features.Neurons
-
Returns status of input neuron evolution.
- isLimited() - Method in class netevo.decoders.RealDecoder
-
Returns the status of limiting real numbers.
- isOutputs() - Method in class netevo.features.Functions
-
Returns status of output neuron AFs.
- isOutputs() - Method in class netevo.features.Neurons
-
Returns status of output neuron evolution.
- isPruneInput() - Method in class netevo.NetEvolver
-
Returns the status of input neuron pruning.
- isPruneOutput() - Method in class netevo.NetEvolver
-
Returns the status of output neuron pruning.
- isValid(double) - Method in class netevo.misc.Matrix
-
Checks if the value is valid.
- isValid(int, int) - Method in class netevo.misc.Matrix
-
Checks if the element has a valid value.
- isValid() - Method in class netevo.misc.NetMatrix
-
Checks if the net has at least one input and one output neuron.
- nameBase - Variable in class netevo.misc.NetReporter
-
File name base string, for saving winner networks.
- net - Variable in class netevo.NetEvolver
-
The evolved net or the template net, if nothing to evolve.
- NetError - Class in netevo.fitness
-
Standard Boone based fitness function returning output neuron errors on a test set.
- NetError(PatternSet) - Constructor for class netevo.fitness.NetError
-
Constructs the fitness function with a test set.
- netErrorString(NeuralNet, PatternSet) - Method in class netevo.misc.NetReporter
-
Prints some error measures for net and patterns.
- netevo - package netevo
-
To start and get an overview, please, look at the
Evolver
base
class.
- netevo.decoders - package netevo.decoders
-
- netevo.features - package netevo.features
-
- netevo.fitness - package netevo.fitness
-
- netevo.misc - package netevo.misc
-
- NetEvoException - Exception in netevo.misc
-
General Netevo exception.
- NetEvoException() - Constructor for exception netevo.misc.NetEvoException
-
- NetEvoException(String) - Constructor for exception netevo.misc.NetEvoException
-
- NetEvoException(Throwable) - Constructor for exception netevo.misc.NetEvoException
-
- NetEvoException(String, Throwable) - Constructor for exception netevo.misc.NetEvoException
-
- netEvolver - Variable in class netevo.Evolver
-
The net evolution master.
- NetEvolver - Class in netevo
-
The base class for neural network evolution.
- NetEvolver(NeuralNet) - Constructor for class netevo.NetEvolver
-
Creates the NetEvolver.
- NetMatrix - Class in netevo.misc
-
A matrix containing all relevant network information.
- NetMatrix(int) - Constructor for class netevo.misc.NetMatrix
-
Constructs an net matrix with three extra columns and all elements marked as unused.
- NetPhenotype - Class in netevo
-
Phenotype implementation for the JEvolution package, using Boone neural networks.
- NetPhenotype() - Constructor for class netevo.NetPhenotype
-
- NetPhenotype(Evolver) - Constructor for class netevo.NetPhenotype
-
Create a new NetPhenotype for the evolution of Boone neural networks.
- NetReporter - Class in netevo.misc
-
Accumulate and print evolution run statistics.
- NetReporter(PrintWriter, String) - Constructor for class netevo.misc.NetReporter
-
Constructs the stat module.
- NEURONS - Static variable in class netevo.features.Feature
-
- Neurons - Class in netevo.features
-
Feature for the evolution of hidden neurons.
- Neurons(Decoder) - Constructor for class netevo.features.Neurons
-
Constructs the feature.
- read(int, int, int) - Method in class netevo.decoders.Decoder
-
Reads the given number of integer values.
- read(int, double, double) - Method in class netevo.decoders.Decoder
-
Reads the given number of double values.
- read(int) - Method in class netevo.decoders.Decoder
-
Reads the given number of bits.
- readBit(int) - Method in class netevo.decoders.BitDecoder
-
Returns the bit at the given index.
- readBit(int) - Method in class netevo.decoders.Decoder
-
Read a bit from the given chromosome.
- readBit(int) - Method in class netevo.decoders.IntDecoder
-
Decode a bit of the chromosome.
- readBit(int) - Method in class netevo.decoders.RealDecoder
-
Returns a bit obeying the limited flag.
- readInt(int, double, double) - Method in class netevo.decoders.BitDecoder
-
Returns the binary-encoded integer.
- readInt(int, double, double) - Method in class netevo.decoders.Decoder
-
Read an integer from the chromosome.
- readInt(int, double, double) - Method in class netevo.decoders.IntDecoder
-
Decodes an integer from the IntChromosome.
- readInt(int, double, double) - Method in class netevo.decoders.RealDecoder
-
Returns the real-encoded integer obeying the limited flag.
- readReal(int, double, double) - Method in class netevo.decoders.BitDecoder
-
Returns the binary-encoded double.
- readReal(int, double, double) - Method in class netevo.decoders.Decoder
-
Read a real value from the chromosome.
- readReal(int, double, double) - Method in class netevo.decoders.IntDecoder
-
Decodes a real from an IntChromosome by simply using readInt().
- readReal(int, double, double) - Method in class netevo.decoders.RealDecoder
-
Returns the real-encoded double obeying the limited flag.
- RealDecoder - Class in netevo.decoders
-
Decoder for RealChromosomes.
- RealDecoder() - Constructor for class netevo.decoders.RealDecoder
-
Constructs the RealDecoder with a gene length of one and without limiting of real numbers.
- RealValues - Class in netevo.features
-
An arbitrary feature described by a number of real values.
- RealValues(Decoder) - Constructor for class netevo.features.RealValues
-
Constructs a single value in the unit interval.
- RealValues(Decoder, int) - Constructor for class netevo.features.RealValues
-
Constructs a number of values in the unit interval.
- RealValues(Decoder, double, double) - Constructor for class netevo.features.RealValues
-
Constructs a single value with min and max value.
- RealValues(Decoder, int, double, double) - Constructor for class netevo.features.RealValues
-
Constructs the feature.
- REG_HINTON - Static variable in class netevo.fitness.RegularizationFactor
-
- REG_LINK - Static variable in class netevo.fitness.RegularizationFactor
-
- REG_NEURON - Static variable in class netevo.fitness.RegularizationFactor
-
The supported types of regularization.
- REG_RUMELHART - Static variable in class netevo.fitness.RegularizationFactor
-
- RegularizationFactor - Class in netevo.fitness
-
Calculator of a regularization factor for network fitness.
- RegularizationFactor(int) - Constructor for class netevo.fitness.RegularizationFactor
-
Constructs regularization of a given type.
- REL_REF_PERIODS - Static variable in class netevo.features.Feature
-
- RelRefPeriods - Class in netevo.features
-
Feature for the evolution of SNN relative refractory periods [ms].
- RelRefPeriods(Decoder) - Constructor for class netevo.features.RelRefPeriods
-
Constructs the feature with default min = 0.0, max = 5.0.
- reportEnd() - Method in class netevo.misc.NetReporter
-
Print global stats after end of evolution.
- RPROP_TRAINING - Static variable in class netevo.features.Feature
-
- RpropTraining - Class in netevo.features
-
Feature to evolve RProp training parameters.
- RpropTraining(Decoder) - Constructor for class netevo.features.RpropTraining
-
Constructs the feature.
- runCount - Variable in class netevo.misc.NetReporter
-
The number of completed runs.
- setAbsRefPeriod(int, double) - Method in class netevo.misc.SpikeMatrix
-
Sets the absolute refractory period in the corresponding column.
- setAbsRefPeriods(List<Double>) - Method in class netevo.SpikingNetEvolver
-
Sets the neurons' absolute refractory periods in the spike matrix.
- setAccelerate(boolean) - Method in class netevo.fitness.Classification
-
Sets the acceleration status.
- setBias(int, double) - Method in class netevo.misc.NetMatrix
-
Sets a value in the bias column.
- setBias(List<Double>) - Method in class netevo.NetEvolver
-
Sets evolved weights in the net matrix.
- setChromosome(Chromosome) - Method in class netevo.decoders.Decoder
-
Sets the chromosome to be decoded.
- setChromosome(List<Chromosome>) - Method in class netevo.decoders.Decoder
-
Sets the chromosome to be decoded from a list of chromosomes.
- setChromosomeNumber(int) - Method in class netevo.decoders.Decoder
-
Sets the chromosome number for this decoder.
- setDecoder(Decoder) - Method in class netevo.features.Feature
-
Sets the decoder used by this feature.
- setDelays(List<Double>) - Method in class netevo.SpikingNetEvolver
-
Stores the evolved link delays in the spike matrix.
- setFunctions(List<Function>, boolean, boolean) - Method in class netevo.NetEvolver
-
Puts the evolved functions on the template neurons in 'topSort', from where they are later
cloned, when the network is constructed.
- setGeneLength(int) - Method in class netevo.decoders.Decoder
-
Sets the length (number of bases) of a gene on the chromosome.
- setGeneLength(int) - Method in class netevo.decoders.IntDecoder
-
Always keeps length at 1.
- setGeneLength(int) - Method in class netevo.decoders.RealDecoder
-
Always keeps length at 1.
- setGeneStart(int) - Method in class netevo.decoders.Decoder
-
Sets the start index of the gene on the chromosome.
- setInputs(boolean) - Method in class netevo.features.Neurons
-
Sets status of input neuron evolution.
- setLimited(boolean) - Method in class netevo.decoders.RealDecoder
-
Sets the limiting of real numbers.
- setLinks(List<Boolean>) - Method in class netevo.NetEvolver
-
Prunes evolved links in the net matrix.
- setMaxValue(double) - Method in class netevo.features.Feature
-
Sets the maximal value to develop.
- setMinValue(double) - Method in class netevo.features.Feature
-
Sets the minimal value to develop.
- setNeurons(List<Boolean>) - Method in class netevo.NetEvolver
-
Prunes evolved neurons in the net matrix.
- setOutputs(boolean) - Method in class netevo.features.Neurons
-
Sets status of output neuron evolution.
- setPatterns(List<Boolean>) - Method in class netevo.TrainEvolver
-
Constructs the training set as a subset of the template set.
- setPrune(int, boolean) - Method in class netevo.misc.NetMatrix
-
Sets the prune status.
- setPruneInput(boolean) - Method in class netevo.NetEvolver
-
Sets the status of input neuron pruning.
- setPruneOutput(boolean) - Method in class netevo.NetEvolver
-
Sets the status of output neuron pruning.
- setRegFactor(RegularizationFactor) - Method in class netevo.fitness.FitnessFunction
-
Sets the regularization factor.
- setRelRefPeriod(int, double) - Method in class netevo.misc.SpikeMatrix
-
Sets the relative refractory period in the corresponding column.
- setRelRefPeriods(List<Double>) - Method in class netevo.SpikingNetEvolver
-
Sets the neurons' relative refractory periods in the spike matrix.
- setThreshold(int, double) - Method in class netevo.misc.SpikeMatrix
-
Sets a value in the threshold column.
- setThresholds(List<Double>) - Method in class netevo.SpikingNetEvolver
-
Stores the evolved threshold values in the spike matrix.
- setTrainer(Trainer) - Method in class netevo.TrainEvolver
-
Sets the trainer to be evolved.
- setType(int, int) - Method in class netevo.misc.NetMatrix
-
Sets a neuron type in the type column.
- setup(Evolver) - Method in class netevo.features.AbsRefPeriods
-
Sets up the feature and its decoder.
- setup(Evolver) - Method in class netevo.features.Bias
-
Sets up the feature and its decoder.
- setup(Evolver) - Method in class netevo.features.BPTraining
-
Sets up the feature parameters.
- setup(Evolver) - Method in class netevo.features.Delays
-
Sets up the feature and its decoder.
- setup(Evolver) - Method in class netevo.features.Feature
-
Sets up the feature parameters.
- setup(Evolver) - Method in class netevo.features.Functions
-
Sets up the feature by counting the number of neurons, for which functions should be evolved.
- setup(Evolver) - Method in class netevo.features.IntValue
-
Sets up the feature parameters.
- setup(Evolver) - Method in class netevo.features.Links
-
Sets up the feature and its decoder.
- setup(Evolver) - Method in class netevo.features.Neurons
-
Sets up the feature by counting the number of neurons to be evolved.
- setup(Evolver) - Method in class netevo.features.Patterns
-
Sets up the feature by counting the total number of patterns, from which a subset shall be evolved.
- setup(Evolver) - Method in class netevo.features.RealValues
-
Sets up the feature parameters.
- setup(Evolver) - Method in class netevo.features.RelRefPeriods
-
Sets up the feature and its decoder.
- setup(Evolver) - Method in class netevo.features.RpropTraining
-
Sets up the feature parameters.
- setup(Evolver) - Method in class netevo.features.Thresholds
-
Sets up the feature and its decoder.
- setup(Evolver) - Method in class netevo.features.Weights
-
Sets up the feature and its decoder.
- setupFields() - Method in class netevo.features.Feature
-
Sets up the fields with correct values.
- setValue(int, int, double) - Method in class netevo.misc.Matrix
-
Sets a matrix elements to the given value.
- setWeight(double) - Method in class netevo.fitness.RegularizationFactor
-
Sets the weight of the factor.
- setWeights(List<Double>) - Method in class netevo.NetEvolver
-
Sets evolved weights in the net matrix.
- SpikeMatrix - Class in netevo.misc
-
A matrix containing all relevant spiking network information.
- SpikeMatrix(int) - Constructor for class netevo.misc.SpikeMatrix
-
Constructs an net matrix with three extra columns and all elements marked as unused.
- SpikingNetEvolver - Class in netevo
-
The base class for the evolution of spiking neural networks evolution.
- SpikingNetEvolver(SpikingNeuralNet) - Constructor for class netevo.SpikingNetEvolver
-
Creates the spiking net evolver.
- SPLINE - Static variable in class netevo.features.Feature
-
- stats - Variable in class netevo.misc.EvoGenStats
-
Stats array: mean/min/max/stdDev for fitness, links, units, cycles.
- statsOut - Variable in class netevo.misc.EvoGenStats
-
Stats writer.
- THRESHOLDS - Static variable in class netevo.features.Feature
-
- Thresholds - Class in netevo.features
-
Feature for the evolution of SNN firing thresholds [mV].
- Thresholds(Decoder) - Constructor for class netevo.features.Thresholds
-
Constructs the feature with default min = 0.0, max = 100.0.
- toString() - Method in class netevo.decoders.Decoder
-
Returns a description of this Feature.
- toString() - Method in class netevo.Evolver
-
Build a string describing the evolution setup and the chromosome structure.
- toString() - Method in class netevo.features.BPTraining
-
Returns a string representation of the feature's BP training parameters.
- toString() - Method in class netevo.features.Feature
-
Returns a description of this Feature.
- toString() - Method in class netevo.features.RpropTraining
-
Returns a string representation of the feature's BP training parameters.
- toString() - Method in class netevo.misc.Matrix
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Returns the matrix in a basic rows/columns string format.
- toString() - Method in class netevo.NetPhenotype
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Returns a string representation of the network.
- toXml(Element) - Method in class netevo.NetPhenotype
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- trainEvolver - Variable in class netevo.Evolver
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The training infrastructure evolution master.
- TrainEvolver - Class in netevo
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Base class for training infrastructure evolution.
- TrainEvolver(NeuralNet, PatternSet) - Constructor for class netevo.TrainEvolver
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Constructs the training evolver with a trainer and a pattern set.
- transferList - Variable in class netevo.decoders.Decoder
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A utility list for data transfer.