Distools User Guide, 2 Hour Course, 4 Day Course
Computing Dissimilarities, Manipulation , Visualization
Dissimilarity Matrix Classification, Dissimilarity Space, PE-Embedding, Evaluation

Visualization

This page belongs to the User Guide of the DisTools Matlab package. It describes some of its commands. Links to other pages are listed above. More information can be found in the pages of the PRTools User Guide. Links are given at the bottom of this page.

Below some ways are shown to visualize a dissimilarity matrix D:

imagesc(+D)  Show the data as an image
LAB = hclust(D,'s',5);
[R,L] = sort(LAB);

imagesc(+D(L,L));
Perform some clustering, rank the labels and use them indices to sort the dissimilarity matrix. Show the result as an image.
scatterd(D*pca(D,2)) Show a PCA space of the dissimilarity space
scatterd(D*pe_em(D,[2 0])) Show first two dimensions of the positive space after PE embedding
scatterd(D*pe_em(D,[1 1])) Show the first positive and the first negative dimension after PE embedding
scatterd(D*mds(D,2)) Multi-dimensional scaling

PRTools User Guide
elements: datasets, datafiles. cells and doubles, mappings, classifiers, mapping types
operations: datasets, datafiles, cells and doubles, mappings, classifiers, stacked, parallel, sequential, dyadic
commands: datasets, representation, classifiers, evaluation, clustering and regression, examples, support

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