Sentence examples for mutual information scoring from inspiring English sources

We specified the mutual information scoring function, a maximum motif size of 15, to perform profile normalization, and to use 100 random replicates in estimating the global FDR.

Association of transcriptional regulators with their target genes, based on expression data, has previously been demonstrated using a number of methods, including mutual information scoring [ 33, 76], probabilistic methods [ 34], differential equations [ 77], Gibbs sampling [ 78] and Spearman correlations [ 31].

To mitigate the inconsistent feature selection issue of regularization, especially the lasso method [9], the framework preanalyzes all features to rank informative features based on mutual information scores [10].

The feature selection criterion based on mutual information score is commonly adopted in literature.

The minimal redundancy between variables is calculated by finding the mutual information scores between variables.

(NMI) Normalized Mutual Information score: is an normalization of the Mutual Information score that measure the mutual information between two clusterings.

To solve the problem, one can assume each feature is independent of all other features, and rank the features in descending order according to their individual mutual information score (I(X_i, Y )).

These relationships were identified using point-wise mutual information scores (PMI) and then used to construct a pathogen similarity tree, which has several interesting features (Fig. 5).

Since we would expect most residues to have strong evolutionary interactions with only a limited number of sites [6], the increased mutual information scores of the unperturbed MSA relative to the randomized MSA likely represent the influence of phylogenetic relationships.

In order to assess similarities and dependence between various methods, Jaccard similarity coefficients, mutual information scores, and Pearson correlation coefficients were calculated for all pairwise comparisons between the seven orthology and three homology identification procedures under consideration.

This difference is measured by the mutual information score.