Sentence examples for model clustering algorithm from inspiring English sources

With a mixture model clustering algorithm, voxel intensities matching particular tissue types were identified.

In order to build accurate model for complicated nonlinear system in engineering, like boiler turbine system, a novel fuzzy-modeling approach is proposed, which is based on a new fuzzy c-regression model (NFCRM) clustering algorithm and is able to determine the right number of rules automatically.

We tested for the existence of a broad genetic stratification in our sample, consisting in K underlying genetically diverged groups (hereafter clusters), using microsatellite data and the model based clustering algorithm implemented in the software Structure (see methods section for details).

A novel hidden Markov model (HMM) and clustering algorithm for the analysis of gene expression time-course data is proposed.

Table 4 Best DER result obtained for both speaker models and clustering algorithms   Clustering algorithm Speaker model HAC ILP GMM 19.45 17.15 I-vectors 16.95 16.10.

The population structure was investigated using the model-based (Bayesian) clustering algorithm implemented in the structure software (Pritchard et al. 2000; Falush et al. 2003), which identifies groups of individuals according to their allele distributions.

We empirically determined that three clusters were appropriate for building a clustering model; beyond three the clustering algorithm saw little improvement.

In this paper, an Integrated Geomorphological Adaptive Neuro-Fuzzy IGANFISce SystemodelANFIS) model conjugated with C-means clustering algorithm was used for rainfall runoff modeling at multiple stations of the Eel River watershed, California.

The expression profiles of these genes could be categorized into nine models by k-means clustering algorithm implemented in program Mayday [ 51].

ADMIXTURE [ 50], which implements a structure-like [ 97] model-based maximum likelihood (ML) clustering algorithm, was used to assess population structure via inferring the individual ancestry proportions.

For acquiring the established network model's width and depth, a clustering algorithm based on density was adopted and a recursion algorithm was designed to solve such problems.