
NTRU
 Referenced in 158 articles
[sw11761]
 suggested by polynomial algebra combined with a clustering principle based on elementary probability theory...

ve08
 Referenced in 142 articles
[sw05141]
 Hessian G(x) of f(x) has clustered eigenvalues at a minimizer x *, in which...

DistAl
 Referenced in 99 articles
[sw01746]
 Each neuron is designed to determine a cluster of training patterns belonging to the same ... strategy to train individual neurons. The individual clusters (represented by the hidden neurons) are combined...

impute
 Referenced in 97 articles
[sw14376]
 input. For example, methods such as hierarchical clustering and Kmeans clustering are not robust...

e1071
 Referenced in 95 articles
[sw07985]
 class analysis, short time Fourier transform, fuzzy clustering, support vector machines, shortest path computation, bagged ... clustering, naive Bayes classifier...

spatstat
 Referenced in 124 articles
[sw04429]
 include dependence on covariates, interpoint interaction, cluster formation and dependence on marks. Fitted models...

SuLQ
 Referenced in 120 articles
[sw11355]
 primitive: principal component analysis, k means clustering, the Perceptron Algorithm, the ID3 algorithm, and (apparently...

Kernlab
 Referenced in 86 articles
[sw07926]
 based machine learning methods for classification, regression, clustering, novelty detection, quantile regression and dimensionality reduction ... methods kernlab includes Support Vector Machines, Spectral Clustering, Kernel PCA, Gaussian Processes...

JMEANS
 Referenced in 67 articles
[sw02649]
 search heuristic for minimum sum of squares clustering. A new local search heuristic, called ... solving the minimum sum of squares clustering problem. The neighborhood of the current solution ... methods, quite substantially when many entities and clusters are considered...

flexmix
 Referenced in 107 articles
[sw06087]
 models, generalized linear models and modelbased clustering...

AutoClass
 Referenced in 68 articles
[sw26092]
 cases, sometimes called finite mixture separation or clustering. The main difference between clustering...

COSA
 Referenced in 45 articles
[sw22936]
 Clustering objects on subsets of attributes. A new procedure is proposed for clustering attribute value ... used in conjunction with conventional distancebased clustering algorithms this procedure encourages those algorithms ... detect automatically subgroups of objects that preferentially cluster on subsets of the attribute variables rather ... relevant attribute subsets for each individual cluster can be different and partially (or completely) overlap...

Cdhit
 Referenced in 46 articles
[sw16887]
 fast program for clustering and comparing large sets of protein or nucleotide sequences. Motivation ... describing an ultrafast protein sequence clustering program called cdhit. This program can efficiently cluster ... limited to only protein sequences clustering, here we present several new programs using the same ... similar matches between them; cdhitest clusters a DNA/RNA sequence database...

sparcl
 Referenced in 47 articles
[sw16353]
 package sparcl: Perform sparse hierarchical clustering and sparse kmeans clustering. Implements the sparse clustering ... framework for feature selection in clustering”; published in Journal of the American Statistical Association...

MOCK
 Referenced in 40 articles
[sw04156]
 benefits of multiple objectives in data clustering In previous work, we have proposed a novel ... approach to data clustering based on the explicit optimization of a partitioning with respect ... complementary clustering objectives. Here, we extend this idea by describing an advanced multiobjective clustering algorithm ... automatically determine the number of clusters in a data set. The algorithm has been subject...

cluster (R)
 Referenced in 45 articles
[sw04571]
 package cluster: Cluster Analysis Extended Rousseeuw et al , Cluster Analysis, extended original from Peter Rousseeuw...

OSCAR
 Referenced in 45 articles
[sw03026]
 Simultaneous regression shrinkage, variable selection, and supervised clustering of predictors with OSCAR. Variable selection ... method, called OSCAR (octagonal shrinkage and clustering algorithm for regression), is proposed to simultaneously select ... variables while grouping them into predictive clusters. In addition to improving prediction accuracy and interpretation ... effect on the response to form predictive clusters represented by a single coefficient. The proposed...

NAMD
 Referenced in 77 articles
[sw03198]
 platforms and tens of processors on commodity clusters using gigabit ethernet. NAMD uses the popular...

MCODE
 Referenced in 43 articles
[sw35748]
 This paper describes a novel graph theoretic clustering algorithm, ”Molecular Complex Detection” (MCODE), that detects ... algorithm has the advantage over other graph clustering methods of having a directed mode that ... allows finetuning of clusters of interest without considering the rest of the network ... allows examination of cluster interconnectivity, which is relevant for protein networks. Protein interaction and complex...

Nimrod/G
 Referenced in 50 articles
[sw09657]
 start from your desktop, local server or cluster; add grid resources (e.g. clusters and Condor...