Uses of Class com.github.raimannma.architecture.EvolveOptions (NEAT 1.14 API)

Packages that use EvolveOptions
Package	Description
com.github.raimannma.architecture

Uses of EvolveOptions in com.github.raimannma.architecture

Methods in com.github.raimannma.architecture that return EvolveOptions
Modifier and Type	Method	Description
`EvolveOptions`	EvolveOptions.`setAmount(int amount)`	Sets amount.
`EvolveOptions`	EvolveOptions.`setClear(boolean clear)`	Sets clear.
`EvolveOptions`	EvolveOptions.`setElitism(int elitism)`	Sets elitism.
`EvolveOptions`	EvolveOptions.`setEqual(boolean equal)`	Sets equal.
`EvolveOptions`	EvolveOptions.`setError(double error)`	Sets error.
`EvolveOptions`	EvolveOptions.`setFitnessFunction(ToDoubleFunction<Network> fitnessFunction)`	Sets fitness function.
`EvolveOptions`	EvolveOptions.`setGrowth(double growth)`	Sets growth.
`EvolveOptions`	EvolveOptions.`setIterations(int iterations)`	Sets iterations.
`EvolveOptions`	EvolveOptions.`setLog(int log)`	Sets log.
`EvolveOptions`	EvolveOptions.`setLoss(Loss loss)`	Sets loss.
`EvolveOptions`	EvolveOptions.`setMaxConnections(int maxConnections)`	Sets max connections.
`EvolveOptions`	EvolveOptions.`setMaxGates(int maxGates)`	Sets max gates.
`EvolveOptions`	EvolveOptions.`setMaxNodes(int maxNodes)`	Sets max nodes.
`EvolveOptions`	EvolveOptions.`setMutationAmount(int mutationAmount)`	Sets mutation amount.
`EvolveOptions`	EvolveOptions.`setMutationRate(double mutationRate)`	Sets mutation rate.
`EvolveOptions`	EvolveOptions.`setMutations(Mutation[] mutations)`	Sets mutations.
`EvolveOptions`	EvolveOptions.`setPopulationSize(int populationSize)`	Sets population size.
`EvolveOptions`	EvolveOptions.`setSelection(Selection selection)`	Sets selection.
`EvolveOptions`	EvolveOptions.`setTemplate(Network template)`	Sets template.

Methods in com.github.raimannma.architecture with parameters of type EvolveOptions
Modifier and Type	Method	Description
`double`	Network.`evolve(double[][] inputs, double[][] outputs, EvolveOptions options)`	Evolves the network to reach a lower error on a dataset using the NEAT algorithm.