Sentence examples for multivariate feature interaction from inspiring English sources

The advantage of an importance score over simple filtering methods (p-value, information gain etc) is that multivariate feature interaction effects may be assessed.

Filter approach is further classified into two categories [20] as univariate (ranking) and multivariate (feature subset).

Some LARP scenarios primarily feature interaction between PCs.

The method proposed here is related to these, except that we propose a multivariate feature selection method and consider parameter estimation using a multivariate shrinkage technique.

SlimPLS is a multivariate feature extraction method which incorporates feature dependencies into calculation.

However unlike psRNAtarget, which measures the miRNA-RNA interaction and gross secondary structure of the mRNA using RNAup program [ 17] at its back-end, p-TAREF prefers to apply dinucleotide density variation profile around the target site as the multivariate feature set for discrimination through statistical machine learning approach, Support Vector Regression.

LARS is a computationally efficient procedure for multivariate feature selection, closely related to Lasso regression [ 27].

Multivariate feature selection approaches could be considered as the closest approximation to the proposed problem.

Another variant being developed includes multivariate feature selection by bootstrapping to select the most significant factors.

Multivariate feature selection was performed using the R-SVM algorithm [ 11].

First, considering feature interaction might improve our classification accuracy.