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The most predictive feature is gene expression in She4 deletion mutants.
The sole focus of most predictive feature selection techniques is on defeating the curse of dimensionality.
Unlike conventional trees, where each node is split using the overall most predictive feature, each node in random forest trees is split using the most predictive feature from a subset of features randomly sampled at that node.
This again is consistent with the results shown in our single feature analysis, where the phyletic retention measure was by far the most predictive feature.
The set of microbiome features used in the cross-donor analysis is taken from the most predictive feature subsets from the previous results, based on the combined Donor A and B data (Fig. 6).
Under this assumption, studies in bacteria identified broader phyletic distributions of essential genes (Jordan et al. 2002; Gerdes et al. 2003), and indeed phyletic retention levels proved to be the most predictive feature of essentiality of bacterial and yeast genes (Gustafson et al. 2006).
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τ = 12hr, accuracy = 84%, most predictive features: 1).
#posts; τ = 24hr, accuracy = 92%, most predictive features: 1).
There are several methods to select the most predictive features in a classification task [42].
In addition, to determine the most predictive features, we rank the features using Chi-square feature selection.
Table 4 Most predictive features in EU and SA according to the Linear SVM with L1 penalty In EU 1.
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