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Entropyology: microarray analysis analogy for digital artifact discrimination

We successfully introduce an analogy of microarray analysis for robust exemplar selection to enable optimal classification. The microarray is analogous to the Spatial Voting (SV) grid, where digital artifacts are stacked onto the grid and grid cells are colored red if only the experiment samples (Class 1) are present, green if only control samples (Class 2) are present, and yellow if both classes are present. We use this information to determine if the exemplars are to be placed in the training, validation, or test dataset. The bytes of these digital artifacts are converted into ASCII values, characterized using the recursive form of higher order parametric and non-parametric statistics, and classifiers derived for discrimination and classification. The results and findings of our work are presented here.