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function [center, U] = vqLBG(data, codeBookSize, dispOpt, kmeansFcn) % vqLBG: Vector quantization using LBG method of center splitting % Usage: [center, U]=vq(data, codeBookSize, dispOpt) % data :

function [M, V, W, logprob] = gmmTrain(data, gaussNum, dispOpt) % gmmTrain: Parameter training for gaussian mixture model (GMM) % Usage: function [M, V, W, logprob] = gmm(data, gaussNum, dispOpt) %

function [new_data, eigvector, eigvalue] = pca(data, eigvector_n) %PCA Principal component analysis % Usage: % [NEW_DATA, EIGVECTOR, EIGVALUE] = PCA(DATA, EIG_N) % % DATA: Rows of vectors of (zer

function out=decisionBoundaryPlot(xx, yy, class, color) % decisionBoundaryPlot: Plot of the decision boundary of a classification problem % Roger Jang, 20041201 if nargin

function [center, U, distortion] = kmeans(dataSet, clusterNum, plotOpt) %KMEANS K-means clustering using Forgy's batch-mode method % Usage: [center, U, distortion] = KMEANS(dataSet, clusterNum) %

/************************************************ * NAME : K44b.H * * Version : 07.MARCH.2000 * ***********************************************/ #ifndef __44B0X_H__ #define _