
SFO
 Referenced in 7 articles
[sw08759]
 allows one to efficiently find provably (near) optimal solutions for large problems. We present ... problems such as feature selection, clustering, inference and optimized information gathering...

clustvarsel
 Referenced in 16 articles
[sw07967]
 variable selection methodology for modelbased clustering which allows to find the (locally) optimal subset...

mlr
 Referenced in 27 articles
[sw12357]
 also an experimental extension for survival analysis, clustering and general, examplespecific costsensitive learning ... optimization techniques, for single and multiobjective problems. Filter and wrapper methods for feature selection...

SimpleMKL
 Referenced in 62 articles
[sw12290]
 combination, we solve a standard SVM optimization problem, where the kernel is defined ... beyond binary classification, for problems like regression, clustering (oneclass classification) or multiclass classification. Experimental ... wavelet kernels and on some model selection problems related to multiclass classification problems...

clustRcompaR
 Referenced in 0 articles
[sw18458]
 hierarchical agglomerative clustering, and kmeans clustering. Selects optimal number of clusters to maximize ”variance...

mbclusterwise
 Referenced in 1 article
[sw27914]
 crossvalidation procedure to select the optimal number of clusters and dimensions...

BALD
 Referenced in 2 articles
[sw20895]
 find the optimal number of clusters, and statistical regression models for SNP selection (Univariate, Lasso...

MALSAR
 Referenced in 4 articles
[sw14319]
 Selection; Robust MultiTask Feature Learning; TraceNorm Regularized MultiTask Learning; Alternating Structural Optimization ... Learning; Robust LowRank MultiTask Learning; Clustered MultiTask Learning; MultiTask Learning with...

SparseFIS
 Referenced in 10 articles
[sw13736]
 rules. Hereby, the number of clusters = rules is predefined and denotes a kind of upper ... reasonable granularity. The second phase optimizes the rule weights in the fuzzy systems with respect ... applying a sparsityconstrained steepest descentoptimization procedure. Depending on the sparsity threshold, weights ... thereby, switching off (eliminating) some rules (rule selection). The third phase estimates the linear consequent...

ACGSSV
 Referenced in 9 articles
[sw20836]
 unconstrained optimization test problems, of different structure and complexity, we prove that selection ... conjugate gradient algorithm ADCG based on clustering the eigenvalues of the iteration matrix defined...

OTclust
 Referenced in 1 article
[sw35615]
 Visualization Selection for Cluster Analysis. Providing mean partition for ensemble clustering by optimal transport alignment...

IPSepCoLa
 Referenced in 9 articles
[sw09789]
 minimum horizontal or vertical separation between selected pairs of nodes. This simple class of linear ... layout of graphs with grouped nodes (called clusters). In the stress majorization forcedirected layout ... considerably faster than using generic constraint optimization techniques and is comparable in speed to unconstrained...

ADPclust
 Referenced in 0 articles
[sw17226]
 href=”http://dx.doi.org/10.1126/science.1242072”>doi:10.1126/science.1242072>. ADPclust clusters data by finding density peaks in a densitydistance ... parameter optimization algorithm, which finds the number of clusters and cluster centroids by comparing average ... silhouettes on a grid of testing clustering results; It also includes a user interactive algorithm ... that allows the user to manually selects cluster centroids from a two dimensional ”densitydistance...

LCE
 Referenced in 5 articles
[sw25277]
 from trivial to select the most effective clustering method and its parameterization, for a particular ... hierarchical clustering in one form or another, this is often suboptimal. Cluster ensemble research...

scalpel
 Referenced in 2 articles
[sw19378]
 dictionary using clustering. Finally, we apply the dictionary in order to select neurons and estimate ... over time, using a sparse group lasso optimization problem. We apply our proposal to three...

Mapper
 Referenced in 1 article
[sw36044]
 Statistical analysis and parameter selection for Mapper. In this article, we study the question ... show that the Mapper is an optimal estimator of the Reeb graph, which gives ... widely used in visualization, clustering and feature selection with the Mapper...

DIDES
 Referenced in 2 articles
[sw33762]
 effective sampling for clustering algorithm. As clustering algorithms become more and more sophisticated to cope ... furthest item from all the already selected ones. Density is managed within a postprocessing step ... avoids many distance calculations thanks to internal optimization. Moreover, it is driven by only...

EPCM
 Referenced in 3 articles
[sw03458]
 selection and/or initialization; (2) the clustering accuracy is often deteriorated due to its coincident clustering ... well labeled, which will weaken its clustering performances in real applications. In this study ... into two parts: the main cluster and auxiliary cluster, and is then utilized to construct ... EPCM is realized by using an alternative optimization approach. The main advantage of EPCM lies...

BFAST
 Referenced in 4 articles
[sw20962]
 Methodology: We introduce a new algorithm specifically optimized for this task, as well ... multithreaded computation on a computer cluster. The new method is based on creating flexible ... indels. Conclusions: We compare BFAST to a selection of largescale alignment tools  BLAT...

Biomine
 Referenced in 2 articles
[sw28409]
 where different edge types are weighted to optimize link prediction accuracy. We also propose ... finding a subset of candidate genes that cluster together in the graph. We experimentally evaluate ... predicting links when a set of selected candidate links is available. The predictions obtained using...