Improving data splitting for classification applications in spectrochemical analyses employing a random-mutation Kennard-Stone algorithm approach
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DOI: 10.1093/bioinformatics/btz421
Abstract: Abstract Motivation Data splitting is a fundamental step for building classification models with spectral data, especially in biomedical applications. This approach is performed following pre-processing and prior to model construction, and consists of dividing the… read more here.
Keywords: classification; algorithm; splitting classification; random mutation ... See more keywords