Pajek Clustering Coefficient

BINOMIAL Binomial coefficient.If the arguments are both non-negative integers with 0

This is a very fast implementation of the original kmeans clustering algorithm without any fancy acceleration technique, such as kd-tree indexing and triangular inequation. (actually the fastest matlab implementation as far as I can tell.)This code is as vectorized as possible. Yet it is very...

The searching process is necessary for the Affinity propagation clustering (AP) when one demands a clustering solution under given number of clusters. The Fast AP uses multi-grid searching to reduce the calling times of AP, and improves the upper bound of preference parameter to reduce the...


Platforms: Matlab

The Gini coefficient is a measure of the inequality of a distribution (often used for income or wealth distributions). The Lorentz curve is a graphical representation of this inequality which is intimately related to the Gini coefficient. The program is straightforward to use. Please consult the...


Platforms: Matlab

Affinity propagation clustering (AP) is a clustering algorithm proposed in "Brendan J. Frey and DelbertDueck. Clustering by Passing Messages Between Data Points. Science 315, 972 (2007)". It has some advantages: speed, general applicability, and suitable for large number of clusters....


Platforms: Matlab

This function computes double block bootstrap percentile confidence intervals and bootstrap standard errors for the Pearson correlation coefficient r and Fisher's z = atanh(r).References:-Efron, B. and R.J. Tibshirani (1993): An Introduction to the Bootstrap, Chapman & Hall.-BdoDshlmann, P. and...


Platforms: Matlab

Performs hierarchical clustering of data using specified method andseraches for optimal cutoff empoying VIF criterion suggested in "Okada Y. et al - Detection of Cluster Boundary in Microarray Data by Reference to MIPS Functional Catalogue Database (2001)".Namely, it searches cutoff where groups...


Platforms: Matlab

This is a tool for K-means clustering. After trying several different ways to program, I got the conclusion that using simple loops to perform distance calculation and comparison is most efficient and accurate because of the JIT acceleration in MATLAB.The code is very simple and well documented,...


Platforms: Matlab

Measure percentage of Accuracy and the Rand index of clustering resultsThe number of class must equal to the number clusterOutput Acc = Accuracy of clustering results rand_index = Rand's Index, measure an agreement of the clustering results match = 2xk matrix which are the best match of the...


Platforms: Matlab

A new soft clustering algorithm is presented (Clustering through Optimal Bayesian Classification). The algorithm does not depend on random initializations, and it contains a native metric to select the optimal number of clusters.The clustering algorithm minimizes the log-Bayesian risk...


Platforms: Matlab

SpectralClustering performs one of three spectral clustering algorithms (Unnormalized, Shi & Malik, Jordan & Weiss) on a given adjacency matrix. SimGraph creates such a matrix out of a given set of data and a given distance function.The code has been optimized to be both fast and memory...


Platforms: Matlab

The code for the spectral graph clustering concepts presented in the following papers is implemented for tutorial purpose:1. Ng, A., Jordan, M., and Weiss, Y. (2002). On spectral clustering: analysis and an algorithm. In T. Dietterich, S. Becker, and Z. Ghahramani (Eds.), Advances in Neural...


Platforms: Matlab

QT clustering algorithm as described in:Heyer, L. J., Kruglyak, S., Yooseph, S. (1999). Exploring expression data: Identification and analysis of coexpressed genes. Genome Research 9,...


Platforms: Matlab

r2 = rsquare(y,f) RSQUARE computes the coefficient of determination (R-square) value from actual data Y and model data F. INPUTS Y : Actual data F : Model fit OUTPUT R2 : Coefficient of determination EXAMPLE x = 0:0.1:10; y = 2.*x + 1 + randn(size(x)); p = polyfit(x,y,1); f = polyval(p,x); r2...


Platforms: Matlab

The STP SecondVirialCoefficient program numerically evaluates the second virial coefficient for the Lennard-Jones potential at various temperatures. The default is temperature range is 0.5 to 5. STP SecondVirialCoefficient is part of a suite of Open Source Physics programs that model aspects of...


Platforms: Mac

Document clustering project is a data mining suite to cluster a document set. This set of tools was implemented from a series of papers: "Clustering Web Pages Semantically using Combinatorial Topology", "Data mining using granular computing", and "A fast association rule algorithm based on bitmap...


Platforms: *nix

A carrier class messaging solution with outstanding technical support, AXIGEN Service Provider Edition provides speed, security and reliability. Its failsafe, intelligent storage system helps you avoid any interruption of service or loss of data. It offers smooth, automatic migration from any...


Platforms: Windows, *nix

Bio::Tools::Run::TribeMCL is a method for clustering proteins into related groups, which are termed protein families. SYNOPSIS use Bio::Tools::Run::TribeMCL; use Bio::SearchIO; # 3 methods to input the blast results # straight forward raw blast output (NCBI or WU-BLAST) my @params =...


Platforms: *nix

HA/FST is a high availability clustering tool for up to four Solaris nodes. HA/FST project supports any application that can be managed from the command line. HA/FST works similar to other HA tools. Heartbeats sent across a private network are monitored. If these heartbeats fail and subsequent...


Platforms: *nix

Text::NSP::Measures::2D::CHI::phi is a Perl module that implements Phi coefficient measure for bigrams. SYNOPSIS Basic Usage use Text::NSP::Measures::2D::CHI::phi; my $npp = 60; my $n1p = 20; my $np1 = 20; my $n11 = 10; $phi_value = calculateStatistic( n11=>$n11, n1p=>$n1p, np1=>$np1,...


Platforms: *nix