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The larger variety of pathway annotations for the genes selected by the GA reaffirms that this feature selection method selects a broader variety of biomarkers related to different aspects of pluripotency.
The method selects a suitable parallel mechanism and a convenient general arrangement.
The method selects a sample of thickness minima such that the data is compatible with the assumptions of EVA.
The MSD method selects a control structure systematically by minimizing the sum of square deviations (SSD) and net load evaluation (NLE) indexes.
For each edge in the application core graph, the proposed method selects a particular path amongst all possible paths, between two grid points.
The method selects a subset of frequent tags that occur in domains called pivots or DI tags.
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Based on genotyping information, our method selects an optimized training population, which will be phenotyped after selection.
The compromising method selects an alternative that is closest to the ideal solution.
In contrast to the Maxmin method, the Maxmax method selects an alternative by its best attribute value.
The Otsu method selects an optimal threshold by maximizing the class variance and it works well when the entire distribution is segmented into two classes.
The DoE method selects an optimal set of m sample configurations (equivalently, the matrix H in (18) corresponding to the m selected sample configurations) using a D-optimal design approach.
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