#include <shark/Models/LinearModel.h>#include <shark/Models/ConcatenatedModel.h>#include <shark/Models/FFNet.h>#include <shark/Algorithms/Trainers/NormalizeComponentsUnitVariance.h>#include <shark/Algorithms/Trainers/LinearRegression.h>#include <shark/Data/DataDistribution.h>#include <shark/ObjectiveFunctions/Loss/SquaredLoss.h>#include <iostream>Go to the source code of this file.
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| int | main () |
| int main | ( | ) |
Our problem: z = sin(x)/x+y+noise
Definition at line 46 of file elmTutorial.cpp.
References shark::random::globalRng, shark::initRandomNormal(), shark::inputDimension(), shark::LabeledData< InputT, LabelT >::inputs(), shark::labelDimension(), shark::LabeledData< InputT, LabelT >::labels(), shark::LinearModel< InputType, ActivationFunction >::matrix(), shark::LinearModel< InputType, ActivationFunction >::offset(), shark::LinearRegression::train(), shark::NormalizeComponentsUnitVariance< DataType >::train(), and shark::transformInputs().