double evalDerivative(
RealMatrix const&,
RealMatrix const& prediction,
RealMatrix& gradient
) const {
gradient.resize(prediction.size1(),prediction.size2());
gradient.clear();
return 0;
}
TestFunction(bool noisy):A(3,3),m_noisy(noisy)
{
A.clear();
A(0,0)=20;
A(1,1)=10;
A(2,2)=5;
m_features|=Base::HAS_FIRST_DERIVATIVE;
}
void CMACMap::eval(RealMatrix const& patterns,RealMatrix &output) const {
SIZE_CHECK(patterns.size2() == m_inputSize);
std::size_t numPatterns = patterns.size1();
output.resize(numPatterns,m_outputSize);
output.clear();
for(std::size_t i = 0; i != numPatterns; ++i) {
std::vector<std::size_t> indizes = getIndizes(row(patterns,i));
for (std::size_t o=0; o!=m_outputSize; ++o) {
for (std::size_t j = 0; j != m_tilings; ++j) {
output(i,o) += m_parameters(indizes[j] + o*m_parametersPerTiling);
}
}
}
}