Sentence examples for iteratively the number of from inspiring English sources

If it is not the case, we have to decrease iteratively the number of components until the independence is reached.

The idea is to iteratively maximize the number of data packets included in (mathcal {S}_{m}).

This process can be repeated iteratively until the number of shared markers between the two sets is maximized.

The Gaussian components are merged iteratively until the number of components in M i is below a preset threshold.

The authors of [4] use a robust estimation method to iteratively estimate the number of layers and the pixel assignments to each layer.

Since the patients have been sorted by decreasing order of readmission probability and number of patients in analysis is constant, it is possible to iteratively increase the number of patients to intervene until a minimum cost is achieved.

Last, parsimony is used to iteratively restrict the number of haplotypes.

The NetGenerator algorithm implements both observations by an iterative development of the state-space system (2) by including coupled sub-models for each time series based on a structure optimisation iteratively increasing the number of connections.

In this method, termed hereafter unmixing-via-NPBN (UNPBN), a flexible number of Gaussian Bayesian networks is being fitted to the data and thereby iteratively identifying the number of distinct subpopulations, unmixing the observations and resolving the statistical model for each subpopulation.

To rule out the possibility that the signature detected by these methods could be identified by simple clustering, we also run K-means by iteratively increasing the number of clusters until one of them matches the pattern of well-positioned nucleosomes (i.e. not enriched, enriched, not enriched in three consecutive windows 60, 30, 60 bp long).

Taking the clustering of strains based on the 50 median-ranked genes as the gold standard, we subsequently deduced the set of minimum median-ranked genes needed to recover the same clustering by iteratively reducing the number of median-ranked genes used and checking the resulting change in clustering topology.