文件名称：Matlab降维工具箱
文件大小：980KB
文件格式：GZ
更新时间：2021-09-16 03:02:56
Dimenson red
常用Matlab降维软件包包括真实有效的多种降维算法： - Principal Component Analysis ('PCA') - Linear Discriminant Analysis ('LDA') - Multidimensional scaling ('MDS') - Isomap ('Isomap') - Landmark Isomap ('LandmarkIsomap') - Locally Linear Embedding ('LLE') - Laplacian Eigenmaps ('Laplacian') - Hessian LLE ('HessianLLE') - Local Tangent Space Alignment ('LTSA') - Diffusion maps ('DiffusionMaps') - Kernel PCA ('KernelPCA') - Generalized Discriminant Analysis ('KernelLDA') - Stochastic Neighbor Embedding ('SNE') - Neighborhood Preserving Embedding ('NPE') - Linearity Preserving Projection ('LPP') - Stochastic Proximity Embedding ('SPE') - Linear Local Tangent Space Alignment ('LLTSA') - Simple PCA ('SimplePCA') - Probabilistic PCA ('ProbPCA') - Conformal Eigenmaps ('CCA', implemented as an extension of LLE) - Maximum Variance Unfolding ('MVU', implemented as an extension of LLE) - Fast Maximum Variance Unfolding ('FastMVU') - Locally Linear Coordination ('LLC') - Manifold charting ('ManifoldChart') - Coordinated Factor Analysis ('CFA') - Autoencoders using RBM pretraining ('AutoEncoderRBM') - Autoencoders using evolutionary optimization ('AutoEncoderEA')
【文件预览】：
drtoolbox
----Readme.txt(9KB)
----techniques()
--------sym_sne.m(2KB)
--------charting.m(3KB)
--------sparse_nn.m(983B)
--------rbmhidlinear.m(4KB)
--------landmark_isomap.m(3KB)
--------mexCCACollectData2.c(6KB)
--------mexCCACollectData2.mexa64(10KB)
--------dijk.m(4KB)
--------computegr.mexa64(9KB)
--------csdpmac(81KB)
--------dijkstra.dll(9KB)
--------computegr.mexglx(6KB)
--------hillclimber2c.m(1KB)
--------computegr.c(3KB)
--------autoencoder.m(3KB)
--------csdp.m(5KB)
--------dijkstra.mexglx(17KB)
--------backprop.m(5KB)
--------diffusion_maps.m(3KB)
--------cfa.m(6KB)
--------cg_update.m(4KB)
--------jdqr.m(71KB)
--------mgs.m(995B)
--------gda.m(4KB)
--------dijkstra.mexa64(21KB)
--------pca.m(2KB)
--------cca.m(15KB)
--------mexCCACollectData.c(8KB)
--------entropy.m(1KB)
--------mexCCACollectData.mexglx(9KB)
--------dijkstra.mexmaci(25KB)
--------spca.m(2KB)
--------lle.m(4KB)
--------writesdpa.m(8KB)
--------fibheap.h(3KB)
--------lda.m(2KB)
--------autoencoder_ea.m(7KB)
--------iterative_spca.m(874B)
--------csdp.exe(1.06MB)
--------laplacian_eigen.m(3KB)
--------llc.m(4KB)
--------fa.m(2KB)
--------npe.m(3KB)
--------readsol.m(4KB)
--------components.m(2KB)
--------mexCCACollectData.dll(7KB)
--------mexCCACollectData.mexmaci(17KB)
--------mexCCACollectData.mexa64(12KB)
--------computegr.dll(7KB)
--------isomap.m(2KB)
--------run_llc.m(2KB)
--------L2_distance.m(2KB)
--------spe.m(4KB)
--------jdqz.m(77KB)
--------ltsa.m(3KB)
--------infermfa.m(2KB)
--------mexCCACollectData2.dll(8KB)
--------lltsa.m(3KB)
--------find_nn.m(3KB)
--------sdecca2.m(9KB)
--------dijkstra.m(2KB)
--------minimize.m(8KB)
--------gram.m(2KB)
--------hill_obj.m(792B)
--------mexCCACollectData2.mexglx(8KB)
--------welcome.m(1KB)
--------find_nn_adaptive.m(3KB)
--------kernel_function.m(5KB)
--------find_nn.c(4KB)
--------rbm.m(4KB)
--------sne.m(4KB)
--------csdpmaci(88KB)
--------mds.m(2KB)
--------dijkstra.cpp(27KB)
--------csdplinux(1.62MB)
--------em_pca.m(3KB)
--------mexCCACollectData2.mexmaci(17KB)
--------fastmvu.m(4KB)
--------lpp.m(3KB)
--------computegr.mexmaci(13KB)
--------kernel_pca.m(4KB)
--------mppca.m(5KB)
--------hlle.m(4KB)
----generate_data.m(4KB)
----intrinsic_dim.m(9KB)
----out_of_sample.m(3KB)
----mexall.m(1KB)
----Contents.m(62B)
----out_of_sample_est.m(2KB)
----compute_mapping.m(15KB)
----prewhiten.m(2KB)