NOTE: The same help can be found from the functions themselves (in most cases).
Try command 'help <function_name>' or 'type <function_name>' in Matlab prompt.

Grouped by function

Demos

som_demo1: SOM Toolbox demo 1: basic properties

som_demo2: SOM Toolbox demo 2: basic usage

som_demo3: SOM Toolbox demo 3: visualization

som_demo4: SOM Toolbox demo 4: data analysis

Creation of structs

som_set: create & set (& check) values to structs

som_info: print out information on a given struct

som_data_struct: create & initialize a data struct

som_map_struct: create & initialize a map struct

som_topol_struct: create & initialize a topology struct

som_train_struct: create & initialize a train struct

som_clstruct: create a cluster struct

som_clset: set properties in a cluster struct

som_clget: get stuff from a cluster struct

Struct conversion and file I/O

som_vs1to2: converts a version 1.0 struct to version 2.0 struct

som_vs2to1: converts a version 2.0 struct to version 1.0 struct

som_read_data: reads a (SOM_PAK format) ASCII data file

som_write_data: writes a SOM_PAK format codebook file

som_write_cod: writes a SOM_PAK format data file

som_read_cod: reads a SOM_PAK format codebook file

Data preprocessing

som_normalize: normalize data set

som_denormalize: denormalize data set

som_norm_variable: (de)normalize one variable

preprocess: preprocessing GUI

Initialization and training functions

som_make: create, initialize and train a SOM

som_randinit: random initialization algorithm

som_lininit: linear initialization algorithm

som_seqtrain: sequential training algorithm

som_batchtrain: batch training algorithm

som_gui: SOM initialization and training GUI

som_prototrain: a simple version of sequential training: easy to modify

Clustering algorithms

som_kmeans: k-means algorithm

kmeans_clusters: try and evaluate several k-means clusterings

neural_gas: neural gas vector quantization algorithm

som_linkage: hierarchical clustering algorithms

som_cllinkage: hierarchical clustering of SOM

som_dmatminima: local minima from distance (or U-) matrix

som_dmatclusters: distance (or U-) matrix based clustering

som_clspread: spreads clusters to unassinged map units

som_cldist: calculate distances between clusters

som_gapindex: gap validity index of clustering

db_index: Davies-Bouldin validity index of clustering

Supervised/classification algorithms

som_supervised: supervised SOM algorithm

lvq1: LVQ1 algorithm

lvq3: LVQ3 algorithm

knn: k-NN classification algorithm

knn_old: k-NN classification algorithm (old version)

SOM error measures

som_quality: quantization and topographic error of SOM

som_distortion: SOM distortion measure

som_distortion3: elements of the SOM distortion measure

Auxiliary functions

som_bmus: calculates BMUs for given data vectors

som_eucdist2: pairwise squared euclidian distances between vectors

som_mdist: calculates pairwise distances between vectors

som_divide: extract subsets of data based on map

som_label: give labels to map units

som_label2num: rcodes string data labels to interger class labels

som_autolabel: automatically labels the SOM based on given data

som_unit_coords: calculates coordinates in output space for map units

som_unit_dists: distances in output space between map units

som_unit_neighs: units in 1-neighborhood for each map unit

som_neighborhood: calculates neighborhood matrix for the given map

som_neighbors: calculates different kinds of neighborhoods

som_neighf: calculates neighborhood function values

som_select: GUI for manual selection of map units

som_estimate_gmm: create Gaussian mixture model on top of SOM

som_probability_gmm: evaluate Gaussian mixture model

som_ind2sub: from linear index to subscript index

som_sub2ind: from subscript index to linear index

som_ind2cod: from linear index to SOM_PAK linear index

som_cod2ind: from SOM_linear index to SOM_PAK linear index

nanstats: mean, std and median which ignore NaNs

som_modify_dataset: add, remove, or extract samples and components

som_fillnans: fill NaNs in a data set based on given SOM

som_stats: statistics of a data set

som_drmake: calculate descriptive rules for a cluster

som_dreval: evaluate descriptive rules for a cluster

som_drsignif: rule significance measures

Using SOM_PAK from Matlab

som_sompaktrain: uses SOM_PAK to train a map

sompak_gui: GUI for using SOM_PAK from Matlab

sompak_init: call SOM_PAK's initialization programs from Matlab

sompak_init_gui: GUI for using SOM_PAK's initialization from Matlab

sompak_rb_control: an auxiliary function for sompak_*_gui functions.

sompak_sammon: call SOM_PAK's Sammon program from Matlab

sompak_sammon_gui: GUI for using SOM_PAK's Sammon program from Matlab

sompak_train: call SOM_PAK's training program from Matlab

sompak_train_gui: GUI for using SOM_PAK's training program from Matlab

Visualization

som_show: basic visualization

som_show_add: add labels, hits and trajectories

som_show_clear: remove extra markers

som_recolorbar: refresh/reconfigure colorbars

som_show_gui: GUI for using som_show and associated functions

som_grid: visualization of SOM grid

som_cplane: component planes and U-matrices

som_barplane: bar chart visualization of map

som_pieplane: pie chart visualization of map

som_plotplane: plot chart visualization of map

som_trajectory: launches a GUI for presenting comet-trajectories

som_dendrogram: visualization of clustering tree

som_plotmatrix: pairwise scatter plots and histograms

som_order_cplanes: order and visualize the component planes

som_clplot: plots of clusters (based on cluster struct)

som_projections_plot: projections plots (see som_projections)

som_stats_plot: plots of statistics (see som_stats)

Auxiliary functions for visualization

hits: calculates hits, or sum of values for each map unit

som_hits: calculates the response of data on the map

som_umat: calculates the U-matrix

cca: curvilinear component analysis projection algorithm

pcaproj: principal component projection algorithm

sammon: Sammon's mapping projection algorithm

som_connection: connection matrix for map

som_vis_coords: map unit coordinates used in visualizations

som_colorcode: create color coding for map/2D data

som_bmucolor: colors of the BMUs from a given map color code

som_normcolor: simulate indexed colormap

som_clustercolor: color coding which depends on clustering structure

som_kmeanscolor: color coding according to k-means clustering

som_kmeanscolor2: a newer version of the som_kmeanscolor function

som_fuzzycolor: a fuzzy color coding

som_coloring: a SOM-based color coding

som_projections: calculates a default set of projections

Report generation stuff

som_table_struct: creates a table struct

som_table_modify: modifies a table struct

som_table_print: print a table in various formats

rep_utils: various utilities for printing report elements

som_stats_table: a table of data set statistics

som_stats_report: report on data set statistics

Low level routines used by visualization functions

vis_patch: defines hexagonal and rectangular patches

vis_som_show_data: returns UserData and subplot handles stored by som_show.m

vis_valuetype: used for type checks

vis_footnote: adds a movable text to the current figure

vis_trajgui: the actual GUI started by som_trajectory.m

vis_PlaneAxisProperties: set axis properties in visualization functions

vis_footnoteButtonDownFcn: callback function for vis_footnote.m

vis_planeGetArgs: converts topol struct to lattice, msize argument pair

vis_show_gui_comp: internal function used by som_show_gui.m

vis_show_gui_tool: internal function used by som_show_gui.m

Other

somtoolbox: this file

iris.data: IRIS data set (used in demos)

License.txt: GNU General Public License

Copyright.txt: Copyright notice

Contents: Overview of SOM Toolbox functions

Alphabetical order