eneural_net 1.1.3

AI Library to create efficient Artificial Neural Networks. Computation uses SIMD (Single Instruction Multiple Data) to improve performance.

1.1.3

• ANN:
  • Added toJson, toJsonMap and fromJson.
• Layer:
  • Added toJson, toJsonMap and fromJson.
• ActivationFunction:
  • Added toJson, toJsonMap, fromJson and byName.
• Scale:
  • Added format.
  • Added toJson, toJsonMap and fromJson.
• Signal:
  • Added format and fromFormat.
  • Optimize values implementation for each format.
• Propagation remove unused _layersPreviousGradientsDeltas.
• Extension ListExtension:
• Added asDoubles and asInts.

1.1.2

• ActivationFunctionSigmoid:
  • Changed to use new faster dart:math.exp function.

1.1.1

• ActivationFunction:
  • Added base class ActivationFunctionFloat32x4.
  • SIMD Optimization:
    • Improved performance in 2x.
    • ActivationFunctionLinear, ActivationFunctionSigmoid, ActivationFunctionSigmoidFast, ActivationFunctionSigmoidBoundedFast.
• eneural_net_fast_math.dart:
  • exp: Improved performance and input range bounded to -87..87.
  • expFloat32x4: new SIMD Optimized Exponential function.
• Chronometer:
  • Improved toString numbers.
  • Comparable.
  • operator +.
• eneural_net_extensions:
  • Improved extensions.
  • Improved documentation.
• Training:
  • Added logProgressEnabled.
• intl: ^0.17.0

1.1.0

• ActivationFunction:
  • Added field flatSpot for derivativeEntryWithFlatSpot().
  • Added ActivationFunctionLinear.
  • ActivationFunctionSigmoid: activation with bounds (-700 .. 700).
• Improved collections and numeric extensions.
• Improved DataStatistics and add CSV generator.
• Signal:
  • Added SIMD related operations.
  • Added: computeSumSquaresMean, computeSumSquares, valuesAsDouble.
  • Set extra values (out of length range): setExtraValuesToZero, setExtraValuesToOne, setExtraValues.
  • Improved documentation.
• Sample:
  • Input/Output statistics and proximity.
• Added SamplesSet:
  • With per set computed defaultTargetGlobalError.
  • Automatic removeConflicts.
• Training:
  • Split into Propagation and ParameterStrategy, allowing other algorithms.
  • Added Backpropagation with SIMD, smart learning rate and smart momentum.
  • Added iRprop+.
  • Added TrainingLogger.
  • Added selectInitialANN.
• ANN:
  • Optional bias neuron.
  • Allow different ActivationFunction for each layer.

1.0.2

• Expose fast math as an additional library.

1.0.1

• README.md:
  • Improve text.
  • Improve activation function text.
  • Fix example.

1.0.0

• Initial version.
• Training algorithms: Backpropagation.
• Activation functions: Sigmoid and approximation versions.
• Fast math functions.
• SIMD: Float32x4