文件名称:drtoolbox
- 所属分类：
- 人工智能/神经网络/遗传算法
- 资源属性：
- [Matlab] [源码]
- 上传时间：
- 2013-03-24
- 文件大小：
- 1.94mb
- 下载次数：
- 0次
- 提 供 者：
- jd***
- 相关连接：
- 无
- 下载说明：
- 别用迅雷下载，失败请重下，重下不扣分！
介绍说明－－下载内容均来自于网络，请自行研究使用
Matlab针对各种数据预处理的降维方法，源码集合。-Currently, the Matlab Toolbox for Dimensionality Reduction contains the following techniques:
Principal Component Analysis (PCA)
Probabilistic PCA
Factor Analysis (FA)
Sammon mapping
Linear Discriminant Analysis (LDA)
Multidimensional scaling (MDS)
Isomap
Landmark Isomap
Local Linear Embedding (LLE)
Laplacian Eigenmaps
Hessian LLE
Local Tangent Space Alignment (LTSA)
Conformal Eigenmaps (extension of LLE)
Maximum Variance Unfolding (extension of LLE)
Landmark MVU (LandmarkMVU)
Fast Maximum Variance Unfolding (FastMVU)
Kernel PCA
Generalized Discriminant Analysis (GDA)
Diffusion maps
Stochastic Neighbor Embedding (SNE)
Symmetric SNE (SymSNE)
new: t-Distributed Stochastic Neighbor Embedding (t-SNE)
Neighborhood Preserving Embedding (NPE)
Locality Preserving Projection (LPP)
Linear Local Tangent Space Alignment (LLTSA)
Stochastic Proximity Embedding (SPE)
Mu
Principal Component Analysis (PCA)
Probabilistic PCA
Factor Analysis (FA)
Sammon mapping
Linear Discriminant Analysis (LDA)
Multidimensional scaling (MDS)
Isomap
Landmark Isomap
Local Linear Embedding (LLE)
Laplacian Eigenmaps
Hessian LLE
Local Tangent Space Alignment (LTSA)
Conformal Eigenmaps (extension of LLE)
Maximum Variance Unfolding (extension of LLE)
Landmark MVU (LandmarkMVU)
Fast Maximum Variance Unfolding (FastMVU)
Kernel PCA
Generalized Discriminant Analysis (GDA)
Diffusion maps
Stochastic Neighbor Embedding (SNE)
Symmetric SNE (SymSNE)
new: t-Distributed Stochastic Neighbor Embedding (t-SNE)
Neighborhood Preserving Embedding (NPE)
Locality Preserving Projection (LPP)
Linear Local Tangent Space Alignment (LLTSA)
Stochastic Proximity Embedding (SPE)
Mu
(系统自动生成,下载前可以参看下载内容)
下载文件列表
._reconstruction_error.m
compute_mapping.m
Contents.m
drgui.m
generate_data.m
intrinsic_dim.m
mexall.m
out_of_sample.m
out_of_sample_est.m
prewhiten.m
reconstruction_error.m
._Readme.txt
Readme.txt
za.txt
降维方法目录.txt
gui\._adaptive_callback.m
...\._case1.m
...\._choose_method.fig
...\._choose_method.m
...\._ded.m
...\._drtool.fig
...\._drtool.m
...\._lnst.m
...\._load_data.fig
...\._load_data.m
...\._load_data_1_var.fig
...\._load_data_1_var.m
...\._load_data_vars.fig
...\._load_data_vars.m
...\._load_xls.fig
...\._load_xls.m
...\._mapping_parameters.fig
...\._mapping_parameters.m
...\._not_calculated.fig
...\._not_calculated.m
...\._not_loaded.fig
...\._not_loaded.m
...\._no_history.fig
...\._no_history.m
...\._plot12n.m
...\._plotn.m
...\._scatter12n.m
...\._scattern.m
...\._update_kernel_uipanel.m
...\._update_type_uipanel.m
...\adaptive_callback.m
...\case1.m
...\choose_method.fig
...\choose_method.m
...\ded.m
...\drtool.fig
...\drtool.m
...\lnst.m
...\load_data.fig
...\load_data.m
...\load_data_1_var.fig
...\load_data_1_var.m
...\load_data_vars.fig
...\load_data_vars.m
...\load_xls.fig
...\load_xls.m
...\mapping_parameters.fig
...\mapping_parameters.m
...\not_calculated.fig
...\not_calculated.m
...\not_loaded.fig
...\not_loaded.m
...\no_history.fig
...\no_history.m
...\plot12n.m
...\plotn.m
...\scatter12n.m
...\scattern.m
...\update_kernel_uipanel.m
...\update_type_uipanel.m
techniques\._autoencoder_ea.m
..........\._backprop.m
..........\._backprop_gradient.m
..........\._cca.m
..........\._cfa.m
..........\._cg_update.m
..........\._charting.m
..........\._checkgrad.m
..........\._combn.m
..........\._components.m
..........\._compute_recon_err.m
..........\._csdp.m
..........\._diffusion_maps.m
..........\._dijk.m
..........\._dijkstra.cpp
..........\._dijkstra.m
..........\._em_pca.m
..........\._fa.m
..........\._fastmvu.m
..........\._find_nn.m
..........\._find_nn_adaptive.m
..........\._gda.m
..........\._gplvm.m
..........\._gplvm_grad.m
..........\._gram.m