%%   DisTools Table of Contents
%%  23-Nov-2009_17:27
%%
%%  This Matlab toolbox for the analysis of dissimilarity data works only 
%%  if also the pattern recognition toolbox PRTools is available.
%%  See http://prtools.org
%%
%%    E. Pekalska,  ela.pekalska@googlemail.com, University of Manchester
%%    R.P.W. Duin,  r.duin@ieee.org, Delft University of Technology
%%
%% Characterization of dissimilarity matrices
%% ------------------------------------------
%% CHECKEUCL    Check whether a square dissimilarity matrix has a Euclidean behavior
%% CHECKTR      Check whether a square dissimilarity matrix obeys triangle inequality
%% CHARDMAT     Fiand several characteristic of (dis)similarity data
%% CORRTR       Correct a square dissimilarity matrix to obey the triangle inequality
%% DISCHECK     Dissimilarity matrix check
%% DISNORM      Normalization of a dissimilarity matrix
%% DISSTAT      Basic statistics of the dissimilarity matrix
%  GOFCL        Goodness of clusters/classes separability vs compactness for dissimilarity data
%  INTRDIM      Estimate Intrinsic dimension from dissimilarity data
%% ISSQUARE     Check whether a matrix is square
%% ISSYM        Check whether a matrix is symmetric
%% ASYMMETRY    Compute asymmetry of dissimilarity matrix
%% NEF          Negative Eigen Fraction
%% NNE          Leave-one-out Nearest Neighbor error on a dissimilarity matrix
%% NNERR        Exact expected NN error from a dissimilarity matrix
%  NNERROR      Exact expected NN error from a dissimilarity matrix (2)
%  VAT          Visual Assessment of cluster Tendency for dissimilarity matrices	
% 
%% 
%% Dissimilarity Measures
%% -----------------------------------------------
%  BINDISTM     Dissimilarity matrix between binary vectors
%  BLURDISTM    Blurred Euclidean distance matrix between blobs
%   BLOBBOX     Find box around a binary blob and resample
%  CORRDISTM    Distance matrix based on correlations
%% COSDISTM     Distance matrix based on inner products
%  DPROCRUSTDM  Distance matrix between datasets based on extended Procrustes problem
%  EDGEDISTM    Distance matrix between images based on their edges
%  EDITDISTM    Edit distance matrix between strings
%% EUDISTM      Euclidean distance matrix
%  EXPDISTM     Exponential-type of distance matrix
%  FLPDISTM     Fast computation of the lp (p > 0)  distance matrix
%% HAMDISTM     Hamming distance matrix between binary vectors
%% HAUSDM       Hausdorff and modified Hausdorff distance between datasets of image blobs
%  JACSIMDISTM  Jaccard-like distance matrix based on similarities
%  LPDISTM      l_p (p > 0) distance matrix
%  QDISTM       Distance matrix for quantitative variables
%  RANKDISTM    Distance matrix between two data sets based on ranking
%  SAMDISTM     Distance matrix based on Spectral Angular Mapper (SAM)
%  STRKERM      String Kernel Matrix by Lodhi et al
% 
%% 
%% Transformations and projections
%% -----------------------------------------------
%% DISSIMT      Fixed DISsimilarity-SIMilarity transformation
%  KCENTERM     Kernel weighted centering mapping (also for a similarity matrix) 
%% MAKESYM      Make a matrix symmetric
%  PROXXM       Proximity mapping
%  SIGMOID      Element-wise sigmoid tranformation of a matrix
%  FASTMAPD     FastMap; inear projection of Euclidean distances
%% PE_EM        Pseudo-Euclidean embedding (includes Classical Scaling as a special case)	
%  SPHEM        Spherical Embedding
% 
%% 
%% Classification in Pseudo-Euclidean Space and indefinite kernels
%% -----------------------------------------------
%  PE_AFFINE
%% SETSIG       Set PE signature for mappings or datasets
%% GETSIG       Set PE signature for mappings or datasets
%% ISPE_DATASET Test dataset for PE signature setting 
%% ISPE_EM      Test mapping for PE signature setting
%% PE_DISTM     Square pseudo-Euclidean distance between two datasets
%% PE_KERNELM   Compute kernel in PE space
%  PE_LIBSVC    Libsvc for PE spaces
%% PE_MTIMES    Matrix multiplication (inner product) in PE space
%% PE_PARZENC   Parzen classifier in PE space
%% PE_KNNC      KNN classifier in PE space
%% PE_NMC       Nearest mean classifier in PE space
%% PE_EM        Pseudo-Euclidean linear embedding of dissimilarities
%  KEM          Kernel embedding
%% PLOTSPECTRUM Plot spectrum of eigenvalues
%  PSPCA        Pseudo-Euclidean Principal Component Analysis
%
%  Indefinte kernel routines
%  -------------------------
%  IKFD         Indefinite Kernel Fisher discriminant
%  IKPCA        Indefinite Kernel PCA
%
%% 
%% Routines supporting in learning from dissimilarity matrices
%% -----------------------------------------------------------------------
%% CROSSVALD    Cross-validation error for dissimilarity representations
%  CLEVALD      Classifier evaluation (Learning curve)
%% DISSPACES    Compute various spaces out of a dissimilarity matrix
%% GENDDAT      Generate random training and test sets for dissimilarity data
%% GENREP       Generate a representation set
%% GENREPI      Generate indices for representation, learning and testing sets
%% SELCDAT      Select Class Subset from a Square Dissimilarity Dataset
%% PROTSELFD    Forward prototype selection   
%  AUCDLPC      AUC-LP classifier on dissimilarity data
%% DLPC         LP-classifier on dissimilarity (proximity) data
%  DRSSCC       Dissimilarity-based random subspace combining classifier 
%% KNNDC        K-Nearest Neighbor classifier for dissimilarity matrices
%% PARZENDDC    Parzen classifier for dissimilarity matrices
%  KFD          Kernel Fisher Discriminant
%  KSVC         Kernel Support Vector classifier on a kernel matrix
% 	KSVO        Kernel Support Vector Optimizer
%  KSVC_NU      Kernel Support Vector classifier on a kernel matrix; nu-version 
% 	KSVO_NU     Kernel Support Vector Optimizer; nu-version 
%  MCLASSDC     Multi-Class Dissimilarity-based Classifier from Two-Class Discriminants
%% TESTKD       Test k-NN classifier for dissimilarity data
%% TESTPD       Test Parzen classifier for dissimilarity data
%  TQDC         Trade-off Quadratic Discriminant (Regularized Bayes Normal Classifier)
% 
% 
%  Graphs and distances
%  -----------------------------------------------
%  DISTGRAPH    Computes distances in a graph
%  DMSTSPM      Finds the shortest paths along K minimum spanning trees
%  DSPATH       Single shortest path in a (dissimilarity) graph
%  DSPATHS      All shortest paths in a (dissimilarity) Graph
%  GRAPHPATH    Compute shortest paths in a graph
%  KMST         Finds K minimum spanning trees based on a distance matrix
%  MSTPLOT      Plot minimum spanning trees
%  NHGRAPH      Find a neighborhood graph and its shortest paths
%  PLOTGRAPH    Plot a 2D graph
%%
%% EXAMPLES
%% --------
%% CROSSVALD_EX Crossvalidation of several classifiers

%  Superfluous / outdated but still available
%  -------------------------------------------------
%  KPCA, AUGPSEM, PSEM
%  