Sentence examples for using a small subset from inspiring English sources

The Random Forest model performs an implicit feature selection, using a small subset of "strong variables" for the classification only, leading to its superior performance on high dimensional data.

Given our purpose to model a co-authorship network using a small subset of papers, we manually reviewed and verified each of the 72 highly cited network papers in the WoS database to identify any ambiguities.

Compared with only using a small subset of SJs, e.g., IC, a matrix based on all of the SJs avoided a logarithm of zero and therefore did not need to introduce a pseudocount that may bias the distribution of scores.

The probes of a tiling array are more or less equally distributed across the genome instead of using a small subset of probes targeting e.g. ORFs like the Affymetrix PAO1 GeneChip® or other available DNA microarrays.

We have previously reported on associations between some measures used in this paper (i.e., startle reflex, Flanker ERN, and parietal asymmetry), along with a behavioral measure of child defensive reactivity, in a pilot demonstration using a small subset of children included in this report (N ≤ 17; Moser et al., 2015).

When estimating the change in conformational entropy from the experimentally derived order parameters, we are using a small subset of residues for which we have data from both the bound and free states, 61 residues for the WT and 42 for the F97Y mutant.

Compared to PSO SVM, HHPSO SVM obtained higher classification accuracy using a smaller subset of features.

While using a smaller subset size results in the local variations being accurately represented, the influence of local heterogeneities in the material becomes more prominent.

While we lacked data on some fine-scale drivers like microclimate and hydrologic processes for the full set of plots used here, further work could examine how those types of drivers differ among these classifications using a smaller subset of plots for which those data are available.

We found that using a smaller subset of features (∼10 15), we can train a classifier with only slightly lower prediction accuracy (details omitted).

Due to the high internal consistency of this scale future work should assess whether the scale could be refined by using a smaller subset of items.