Two cross-validation techniques to comprehensively characterize global horizontal irradiation regression models: Single data-splitting is insufficient
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Renewable and Sustainable Energy"
DOI: 10.1063/1.5116642
Abstract: Data-splitting is the most widely used method to cross-validate global horizontal irradiation regression models. An available dataset is split into two subsets, one to calibrate models and the other to validate them. This study investigated… read more here.
Keywords: validation; cross validation; data splitting; regression models ... See more keywords
Improving data splitting for classification applications in spectrochemical analyses employing a random-mutation Kennard-Stone algorithm approach
Sign Up to like & getrecommendations! Published in 2019 at "Bioinformatics"
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