示例#1
0
	double evalDerivative(
		RealMatrix const&, 
		RealMatrix const& prediction, 
		RealMatrix& gradient
	) const {
		gradient.resize(prediction.size1(),prediction.size2());
		gradient.clear();
		return 0;
	}
示例#2
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;
	}
示例#3
0
文件: CMAC.cpp 项目: Shark-ML/Shark
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);
            }
        }
    }
}