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Novel split quality measures for stratified multilabel Cross Validation with application to large and sparse gene ontology datasets
We present an extensive comparison of various types of cross validation methods in which we show that optisplit produces more even cross validation splits than the existing methods and that it is fast enough to be used on big Gene Ontology (GO) datasets.
Estimating regression errors without ground truth values
Regression analysis is a standard supervised machine learning method used to model an outcome variable in terms of a set of predictor variables.
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