Sentence examples for most informative attributes from inspiring English sources

The experimental results confirm the efficiency of the proposed approaches in improving the classification accuracy compared to other wrapper-based algorithms, which insures the ability of WOA algorithm in searching the feature space and selecting the most informative attributes for classification tasks.

We conducted data decay analysis to obtain additional insight into the most informative attributes.

To select the most informative attributes for the classification, we used a combination of feature selection methods (Methods) (Additional file 1: Table S6).

Among the most informative attributes, we found HP1α and CTCF downstream of the alternative exon in relation to inclusion events; and AGO1, H3K36me3 and RNAPII in relation to skipping events.

Using the 15 most informative attributes, we used cross-validation with an Alternate Decision tree (ADTree) classifier to obtain 606 (68.552%) correctly labeled events (282 inclusion, 324 skipping) (Additional file 1: Table S7 and Additional file 2) from the original 884 events (receiver operating characteristic (ROC) area 0.735, precision 0.687, recall 0.686).

An analysis of the occurrence frequency of each attribute and its level in the C4.5 bagging trees identified the 10 most informative attributes for the prediction of 72-h total analgesic consumption (i.e., a continuous dose and PCA dose) and the prediction of PCA analgesic consumption only.

The addition of a third attribute does not meaningfully improve the performance of the classifier: the most informative two attribute and three attribute rules both have a cross validation accuracy of 72%.

The most informative homology attributes include percentage, average value, or sum value of a given gene having homologous hits with organisms having different pathogenicity and habitat phenotypes.

Seven of the top ten most informative two-attribute rules contain some combination of energy and surface area terms.

The SMISPs are filtered using the most informative two-attribute rule from Table 3 and the 0.55 SVM score threshold.

We cross-validated our classifier using all possible one, two, and three attribute rules to identify the most accurate and informative attributes.