15 #ifndef __MLPACK_METHODS_KERNEL_PCA_NAIVE_METHOD_HPP
16 #define __MLPACK_METHODS_KERNEL_PCA_NAIVE_METHOD_HPP
23 template<
typename KernelType>
39 arma::mat& transformedData,
43 KernelType kernel = KernelType())
46 arma::mat kernelMatrix;
48 kernelMatrix.set_size(data.n_cols, data.n_cols);
53 for (
size_t i = 0; i < data.n_cols; ++i)
55 for (
size_t j = i; j < data.n_cols; ++j)
58 kernelMatrix(i, j) = kernel.Evaluate(data.unsafe_col(i),
64 for (
size_t i = 1; i < data.n_cols; ++i)
65 for (
size_t j = 0; j < i; ++j)
66 kernelMatrix(i, j) = kernelMatrix(j, i);
73 arma::rowvec rowMean = arma::sum(kernelMatrix, 0) / kernelMatrix.n_cols;
74 kernelMatrix.each_col() -= arma::sum(kernelMatrix, 1) / kernelMatrix.n_cols;
75 kernelMatrix.each_row() -= rowMean;
76 kernelMatrix += arma::sum(rowMean) / kernelMatrix.n_cols;
79 arma::eig_sym(eigval, eigvec, kernelMatrix);
83 for (
size_t i = 0; i < floor(eigval.n_elem / 2.0); ++i)
84 eigval.swap_rows(i, (eigval.n_elem - 1) - i);
87 eigvec = arma::fliplr(eigvec);
89 transformedData = eigvec.t() * kernelMatrix;
Linear algebra utility functions, generally performed on matrices or vectors.
static void ApplyKernelMatrix(const arma::mat &data, arma::mat &transformedData, arma::vec &eigval, arma::mat &eigvec, const size_t, KernelType kernel=KernelType())
Construct the kernel matrix approximation using the nystroem method.