| PRTools |  |
| A Matlab toolbox for pattern recognition | Imported pages from 37Steps |
Clustering and Distances
| distm | Distance matrix between two data sets. | more routines |
| emclust | Expectation – maximization clustering | |
| proxm | Proximity mapping and kernel construction | |
| hclust | Hierarchical clustering | |
| kcentres | k-centres clustering | |
| kmeans | k-means clustering | |
| modeseek | Clustering by modeseeking | |
| mds | Non-linear mapping by multi-dimensional scaling (Sammon) | |
| mds_cs | Linear mapping by classical scaling | |
| mds_init | Initialisation of multi-dimensional scaling | |
| mds_stress | Dissimilarity of distance matrices |
elements: datasets datafiles cells and doubles mappings classifiers mapping types.
operations:datasets datafiles cells and doubles mappings classifiers stacked parallel sequential dyadic.
user commands:datasets representation classifiers evaluation clustering examples support routines.
introductory examples:IntroductionScatterplotsDatasets Datafiles Mappings Classifiers Evaluation Learning curves Feature curves Dimension reductionCombining classifiers Dissimilarities.
advanced examples.