eneural_net library

eNeural.net library.

Classes

ActivationFunction<N extends num, E>
Base class for Activation Functions.
ActivationFunctionFloat32x4
Base class for SIMD optimized functions using Float32x4.
ActivationFunctionLinear
Linear Activation Function (SIMD optimized).
ActivationFunctionSigmoid
Sigmoid Activation Function (SIMD optimized).
ActivationFunctionSigmoidBoundedFast
Fast Pseudo-Sigmoid Activation Function Bounded (SIMD optimized).
ActivationFunctionSigmoidFast
Fast Pseudo-Sigmoid Activation Function (SIMD optimized).
ActivationFunctionSigmoidFastInt
Experimental Integer Sigmoid Function.
ActivationFunctionSigmoidFastInt100
Experimental Integer Sigmoid Function (scale 100).
ANN<N extends num, E, T extends Signal<N, E, T>, S extends Scale<N>>
Artificial Neural Network
Backpropagation<N extends num, E, T extends Signal<N, E, T>, S extends Scale<N>, P extends Sample<N, E, T, S>>
Implementation of Backpropagation training algorithm.
Chronometer
A Chronometer useful for benchmarks.
DataEntry
DataStatistics<N extends num>
HiddenLayerConfig<N extends num, E>
The configuration for the hidden layers.
Layer<N extends num, E, T extends Signal<N, E, T>, S extends Scale<N>>
Base class for ANN layers.
LayerFloat32x4
ANN Layer for Float32x4 types.
LayerHidden<N extends num, E, T extends Signal<N, E, T>, S extends Scale<N>>
Layer specialized for hidden neurons.
LayerInput<N extends num, E, T extends Signal<N, E, T>, S extends Scale<N>>
Layer specialized for input neurons.
LayerInt32x4
ANN Layer for Int32x4 types.
LayerOutput<N extends num, E, T extends Signal<N, E, T>, S extends Scale<N>>
Layer specialized for output neurons.
RProp<N extends num, E, T extends Signal<N, E, T>, S extends Scale<N>, P extends Sample<N, E, T, S>>
Implementation of Resilient Backpropagation (version iRProp+).
Sample<N extends num, E, T extends Signal<N, E, T>, S extends Scale<N>>
Base class for ANN samples.
SampleFloat32x4
ANN sample based in Float32x4 data.
SampleInt32x4
SamplesGenerator
Samples Generator.
SamplesSet<P extends Sample<num, dynamic, dynamic, Scale<num>>>
Samples Set.
Scale<N extends num>
Base class for scales used for ANN, Signal and Sample.
ScaleDouble
A Scale<double>.
ScaleInt
A Scale<int>.
ScaleZoomable<N extends num>
ScaleZoomableDouble
ScaleZoomableInt
Signal<N extends num, E, T extends Signal<N, E, T>>
SignalFloat32x4
SignalFloat32x4Mod4
SignalInt32x4
Training<N extends num, E, T extends Signal<N, E, T>, S extends Scale<N>, P extends Sample<N, E, T, S>>
Base class for training algorithms.

Enums

ActivationFunctionScope
Scope of the activation function.

Functions

defaultTrainingLogger(Training<num, dynamic, Signal<num, dynamic, dynamic>, Scale<num>, Sample<num, dynamic, Signal<num, dynamic, dynamic>, Scale<num>>> training, String type, String message, [dynamic error, StackTrace? stackTrace]) → void
The default TrainingLogger.
DefaultTrainingLogger(Training<num, dynamic, Signal<num, dynamic, dynamic>, Scale<num>, Sample<num, dynamic, Signal<num, dynamic, dynamic>, Scale<num>>> training, String type, String message, [dynamic error, StackTrace? stackTrace]) → dynamic

Typedefs

TrainingBuilder<N extends num, E, T extends Signal<N, E, T>, S extends Scale<N>, P extends Sample<N, E, T, S>> = Training<N, E, T, S, P> Function(ANN<N, E, T, S> ann, SamplesSet<P> samplesSet)
A builder for Training instances.
TrainingLogger = void Function(Training<num, dynamic, Signal<num, dynamic, dynamic>, Scale<num>, Sample<num, dynamic, Signal<num, dynamic, dynamic>, Scale<num>>> training, String type, String message, [dynamic error, StackTrace? stackTrace])
Training logger.