DISTOOLS DisTools: Dissimilarity based pattern recognition
This Matlab toolbox for the analysis of dissimilarity data works only
if also the pattern recognition toolbox PRTools version 5 is available.
See http://prtools.org, http://37steps.com
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| genddat | Generate random training and test sets for dissimilarity data |
| makesym | Make a dissimilarity matrix symmetric |
| seldclass | Select class subset from a square dissimilarity dataset |
| asymmetry | Estimate asymmetry of dissimilarity matrix |
| nef | Compute negative eigen-fraction and negative eigen-ratio |
| nmf | Compute fraction of violations of triangle inequality |
| issquare | Check whether a matrix is square |
| issym | Check whether a matrix is symmetric |
| intrdim | Intrinsic diemensionality |
| nne | Leave-one-out Nearest Neighbor error on a dissimilarity matrix |
| nnerror1 | Exact expected NN error from a dissimilarity matrix |
| nnerror2 | Exact expected NN error from a dissimilarity matrix |
| distm | Square Euclidean distance matrix (PRTools) |
| proxxm | Proximity mappings |
| disnorm | Normalization of a dissimilarity matrix (PRTools) |
| dissimt | Fixed DISsimilarity-SIMilarity transformations |
| makemetric | Make a matrix metric |
| makesym | Make a matrix symmetric |
| pe_em | Pseudo-Euclidean embedding (special case: Classical Scaling) |
| euspace | Convert PE space into an Euclidean space |
| dispn | Split dissimilarity matrix in positive and negative part |
| getspectrum | Retrieve spectrum form pseudo-Euclidean mapping |
| setsig | Set signature for pseudo-Euclidean dataset or mapping |
| getsig | Retrieve signature of PE mapping or PE dataset |
| ispe_dataset | Test dataset for PE signature setting |
| ispe_em | Test mapping for PE signature setting |
| nef | Compute Negative Eigen Fraction from PE dataset or mapping |
| nmf | Compute Non-Metric Fraction from dissimilarity matrix |
| pe_distm | Square pseudo-Euclidean distance between two datasets |
| pe_kernelm | Compute kernel in PE space |
| 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_svc | Support classifier in PE space |
| pe_libsvc | Support classifier in PE space based on LIBSVM |
| pe_em | Pseudo-Euclidean linear embedding |
| plotspectrum | Plot spectrum of eigenvalues |
| seleigs | Select eigenvalues from a list |
| crossvald | Cross-validation error for dissimilarity data |
| clevald | Classifier evaluation (learning curve) for dissimilarity data |
| protselfd | Forward prototype selection |
| dlpc | LP-classifier on dissimilarity (proximity) data |
| knndc | K-Nearest Neighbor classifier for dissimilarity matrices |
| parzenddc | Parzen classifier for dissimilarity matrices |
| testkd | Test k-NN classifier for dissimilarity data |
| testpd | Test Parzen classifier for dissimilarity data |
| disex_spiral | The long spiral example |
| disex_protselfd | Example of forward prototype selection |
| disex_classf | DisTools classf example |
| disex_2dclassf | DisTools 2D classf example |
| PRTools website |