Modified & Generalized Dunn's index by Nejc Ilc

An implementation of Modified and Generalized Dunn's index for internal cluster validation. (clustering, validation, dunns index)

DI=indexDN(data,labels,distance)

[G,d,uniqueInd]=graph_create(data,labels,graph_type,options...

[fig]=scatterPlot(data,labels,options)

clusterData by Brett Shoelson

Clusters an MxN array of data into an unspecified number (P) of bins. (data analysis, group data, cluster)

clusterData(data, sensitivity)

MatClust by Mattias Karlsson

Spike sorting program for extracellular recordings. Version 1.4 (spike sorting, neuroscience, clustering)

CSI()

ExcludeOverlappingPoints(clustnum)

ISIfilter()

Bayesian clustering with outliers and missing data by Gabriel Agamennoni

Object MatLab implementation of the Bayesian Robust Mixture Model (BRMM). (bayesian models, clustering, robust clustering)

TestBRMM()

(ConstructOnLoad) BRMM %#ok

Forel clustering by wadzapi

Forel clustering algothm. (clustering, forel)

forel(X, r)

Fast segmentation of N-dimensional grayscale images by Anton Semechko

Partition N-D grayscale image into c classes using efficient C-means and fuzzy C-means clustering (image segmentation, fuzzy cmeans, cmeans)

DemoFCM

L=LUT2label(im,LUT)

Umap=FM2map(im,U,H)

Infinite Bernoulli mixture by Sam Gershman

Nonparametric Bayesian clustering of binary data. (machine learning, statistics, clustering)

dpmm_bernoulli(X,varargin)

Fast Medoid Selection using MFAMES by Stephen Pratt

An implementation of the (Mutliple) FAst MEdoid Selection algorithm (MFAMES)[Paterlini et al. 2011] (medoid, kmedoids, clustering)

mfames(cluster_members, ...

Mean shift pixel cluster by Yue Wu

This toy code implements the classic and basic pixel clustering using mean shifts (image processing, clustering, statistics)

meanShiftPixCluster(x,hs,hr,th,plotOn)

k-means++ by Laurent S

Cluster multivariate data using the k-means++ algorithm. (clustering, kmeans, data mining)

kmeans(X,k)

Graph Agglomerative Clustering (GAC) toolbox by Wei Zhang

Graph Degree Linkage: Agglomerative Clustering on a Directed Graph. ECCV 2012. (clustering, statistics, data exploration)

gacBuildDigraph_c(distance_matrix, K, a)

gacBuildLlinks_cwarpper(distance_matrix, p, NNIndex)

gacFindKcCluster (affinityTab, Kc)

connected component labeling like bwlabel by michael scheinfeild

recursive function of labeling binary image 4 connected (connected component l..., clustering, bwlabel)

detect(bw);

Kmeans by Wei LI

Kmeans implemented using accumarray (clustering, machine learning)

kmeans(D, k, maxIter)

Generate Data for Clustering by Nuno Fachada

Generates 2D data for clustering. (clustering, data, generator)

generateData( ...

Inverse Optimal Functions for Motoman HP-3 Tip Precision by Alan Jennings

A population based optimization increases pointing precision for a planar robotic arm. (robotics, inverse, inverse kinematics)

PSO_Function_ArmijoRobot_3

PointCluster2Angles_HP5_3

Clusters=ClusterGenerate_4(TestPoint,J,J_Grad,Y_Grad,Option...

A Fast Image Segmentation using Delaunay Triangulation (Revisited) by Abbas Cheddad

This is a tuned version of the old post on Delaunay-based image segmentation. (image segmentation, histogram, delaunay triangulatio...)

DSNew.m

[Segmented Clusters]=DSIterate(Segmented,B,C,D)

Dunn's index by Julian Ramos

This is an implementation of the Dunn's index for clustering. (dunn, measurement, index)

DI=dunns(clusters_number,distM,ind)

dunnsDemo.m

Customized K-Means by Nirmal

Customized K-means where you can choose different initial cluster centroid. (kmeans, clustering)

[class,centroid,counter]=MyKMeans(data,k,option,init_centro...

PSA: Part and Select Algorithm by Alan de Freitas

Partitions the points X into K clusters and also returns the K more representative points. (clustering, part and select algor..., psa)

psa( X, k )

EM algorithm for Gaussian mixture model with background noise by Andrew

Standard EM algorithm to fit a GMM with the (optional) consideration of background noise. (gmm, em, clustering)

GM_EM(X,k,bn_noise,reps,max_iters,tol)

Free Split and Merge Expectation Maximization for MultiVariate Gaussian Mixture by Sebastien PARIS

FSMEM can estimate MVGM parameters and number of conpounds via split/merge cluster moves (split and merge, clustering, signal processing)

test_fsmem_mvgm

gene_mvgm(d , K , sig)

init_mvgm(Z , K)

EM algorithm for Gaussian mixture model by Mo Chen

EM algorithm for Gaussian mixture. Works on arbitray dimensions with high speed and precision. (em, clustering, gmm)

emgm(X, init)

logsumexp(x, dim)

spread(X, label)

K-medoids by Mo Chen

K-medoids clustering algorithm (kmedoids, clustering, kmeans)

kmedoids(X,k)

spread(X, label)

Spherical K-means by Mo Chen

A kmeans like clustering algorithm to cluster data on a unit sphere. (clustering)

spkmeans(X, init)

kmeans clustering by Mo Chen

Fully vectorized kmeans algorithm. Fast yet simple (10 lines) (kmeans, clustering, kmeans code for image...)

litekmeans(X, k)

spread(X, label)

K-means++: kmeans algorithm with smart seeding by Mo Chen

This is an implementation of the paper k-means++: the advantages of careful seeding. (clustering, kmeans, data analysis)

kmeanspp(X, k)

spread(X, label)

Kernel k-means by Mo Chen

kernel k-means algorithm (kernel, kmeans, clustering)

knkmeans(K,init)

spread(X, label)

Color Clustering Matlab by GAGAN

Computes the clusters of Pixels based upon their color. (color, color matlab, clustering)

binary_quant.m

CLUSTERING THROUGH OPTIMAL BAYESIAN CLASSIFICATION by Lionel

The package contains function for performing soft clustering. (statistics, clustering, clusters)

Dis=contrastEM(x,centroids,py_x)

[npy_x,npy,idxClus]=distinctW(w,py_x,py)

[py_x,centroids,clustind,complexity]=EM(x,beta,varargin)

The Adjusted Mutual Information by Xuan Vinh Nguyen

The Adjusted Mutual Information for clustering comparison (clustering, data mining, machine learning)

[AMI_]=AMI(true_mem,mem)

The minCEntropy algorithm for alternative clustering by Xuan Vinh Nguyen

The minCEntropy algorithm for alternative clustering (clustering, alternative clusterin..., data mining)

Cont=Contingency(Mem1,Mem2)

MI(label, result)

[max_mem,max_obj,all_mem,S]=minCEntropy(a,K,sigma_factor,n_...

The Spherical K-means algorithm by Xuan Vinh Nguyen

Clustering on the hypersphere with the Spherical K-means algorithm (kmeans, spherical kmeans, clustering)

[best_x,best_f,best_membership,empty,loop]=SPKmeans(a,K,n_r...

b=normalize_norm(a)

b=normalize_norm_mean(a)

Software implementations of PBKM by qi zhang

advantage of speed & performance appears under large number of clusters (clustering, large number of clust..., clustering algorithm)

IDXA=cut(n,IDX);

IDXA=divKMS(x,K);

T=cengci(x,K);

Clustering results measurement by Praisan Padungweang

Measure percentage of Accuracy and the Rand index of clustering results (measurement, clustering)

[Acc,rand_index,match]=AccMeasure(T,idx)

A Fast Image Segmentation using Delaunay Triangulation by Abbas Cheddad

A fully automated process that does not require initial estimate of number of clusters. (object extraction, cell segmentation, image segmentation)

DS.m

DSeg(varargin)

PlotClusters.m by Elad Kivelevitch

This function plots clustering data, for example the one provided by kmeans, if the data is 2d or 3d (clustering, data exploration, statistics)

[]=PlotClusters(Data,IDX,Centers,Colors)

color Image Segmentation by Athi

Segments a color image into regions. (clustering, segmentation, image segmentation)

colImgSeg(inImg, nBins, winSize, nClass)

SampleUsage.m

Fast K-means by Tim Benham

Fast K-means implementation with optional weights and K-means++ style seeding. (clustering, kmeans, weighted kmeans)

fkmeans(X, k, options)

K-means image segmentation by Pablo Fonseca

K-means image segmentation based on histogram to reduce memory usage which is constant for any size. (clustering, kmeans, image)

kmeansclustering(im, k)

sinspace by Sky Sartorius

Generates a sine-spaced vector with elements clustered at one of the two endpoints (clustered, clustering, sine)

sinspace(d1, d2, n, factor)

cosspace by Sky Sartorius

Generates cosine- or acos-spaced vector with elements clustered or sparse at the endpoints (cosine, spacing, spaced)

cosspace(d1, d2, n, factor)

kmedioids by Benjamin Sapp

Performs kmedioids clustering, requires only a nxn distance matrix D and number of clusters, k. (clustering, k medioids, k centroids)

kmedioids(D,k)

uidendrogram by Malcolm McLean

Interactive dendrogram viewer using nested boxes (dendrogram, clustering, gui)

drawtree(link, cut, colours, iwidth, iheight)

getleaves( link, id )

testuidendrogram

Fast Affinity Propagation Clustering under Given Number of Clusters by Kaijun Wang

Fast searching the given number of clusters (clustering, statistics, fast ap clustering)

[idx,netsim,dpsim,expref,pref,lowp,highp]=apclusterK_fast2(...

[idx,netsim,dpsim,expref,pref]=apclusterK(s,kk,prc);

[idx,netsim,i,unconverged,dpsim,expref]=apcluster(s,p,varar...

Quad-Tree segmentation - MEX by Ahmad

Segments an input image using Quad-trees (quadtree, segmentation, clustering)

quadtreeseg( im, varargin )

KMeans Segmentation - MEX by Ahmad

Given N data elements of R dimensions (N x R matrix), it segregates the n elements into k clusters (kmeans, segmentation, clustering)

kmeansK( data_vecs, k )

Hypergraph edge/vertex matrix by Marcos Bolanos

Convert binary undirected adjacency matrix into a hypergraph matrix. (hypergraph, clusters, adjacency matrix)

Hyper.m

Image segmentation using statistical region merging by Sylvain Boltz

Very simple and fast image segmentation code using statistical region merging. (region merging, clustering, image segmentation)

[maps,images]=srm(image,Qlevels)

srm_getborders(map)

srm_imgGrad(I)

QT Clustering using Euclidean Distance, Jackknife Correlation by Misha Koshelev

Some simple MATLAB files that perform QT clustering (clustering, medicine, genetics)

idx=qtclusteuclid(G,d,D)

idx=qtclustjackknife(G,d,J)

idx=qtclustmod(G,d,D)

Spectral Clustering Algorithms by Asad Ali

Implementation of four key algorithms of Spectral Graph Clustering using eigen vectors : Tutorial (spectral clustering, affinity matrix, graph segmentation)

CalculateAffinity(data)

GenerateData(select)

Jordan_Weiss.m