eneural_net 1.1.0
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AI Library to create efficient Artificial Neural Networks. Computation uses SIMD (Single Instruction Multiple Data) to improve performance.
1.1.0 #
ActivationFunction:- Added field
flatSpotforderivativeEntryWithFlatSpot(). - Added
ActivationFunctionLinear. ActivationFunctionSigmoid: activation with bounds (-700 .. 700).
- Added field
- Improved collections and numeric extensions.
- Improved
DataStatisticsand addCSVgenerator. 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.
- With per set computed
Training:- Split into
PropagationandParameterStrategy, allowing other algorithms. - Added
Backpropagationwith SIMD, smart learning rate and smart momentum. - Added
iRprop+. - Added
TrainingLogger. - Added
selectInitialANN.
- Split into
ANN:- Optional bias neuron.
- Allow different
ActivationFunctionfor 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