Sentence examples for mutual information table from inspiring English sources

In the mining algorithm phase, a recursion method to construct a direct association pattern tree is addressed with an asymmetric mutual information table, and a recursive mining algorithm to find frequent items.

Mutual information (Table 2, top) and Pearson coefficients (Table S1, bottom) are commonly used to measure overall/marginal dependence.

However, synergy index and mutual information statistics (Table S5) failed to show evidence for interaction between neither sex, smoking nor C3.

We computed the mutual information corresponding to that contingency table and chose the frequency cutoff which maximizes it.

More precisely, for every possible frequency difference cutoff we compared the variants obtained at this cutoff with the result of the validation experiment and chose the cutoff for which the mutual information of the corresponding contingency table was maximized.

Several other software programs that can be used for calculating gene gene associations (correlations, mutual information and others) are listed in Table 1.

Specifically, mutual information was calculated using the contingency table obtained by the true partition and the clustering results; since the mutual information has no upper bounds, its normalized version, ranging between 0 and 1, was used [ 24].

For local ancestry estimation, a total of 38 additional SNPs restricted to chromosome 22 were selected for genotyping using the recently reported expected mutual information ancestry measure (32) (Supplementary Material, Table S3).

The mutual information and the transmission power are presented in Table 6 for West Africa and Table 7 for South Korea.

Table 3 The fused mutual information between the source image and the fused images The fused mutual information Proposed fused image DWT fused image Contrast pyramid image FQI 0.5719 0.5719 0.5719.

For example, when q = 20 (Fig.  2a and Table  1), the normalized mutual information between clustering scheme produced by direct concatenation and the true patient clustering scheme is only 0.0354, whereas the normalized mutual information between clustering scheme produced by SNF and the true scheme is 0.00519.