Specifying, assessing, and selecting among candidate statistical models is fundamental to
ecological research. Commonly used approaches to model selection are based on …

Partial least squares-discriminant analysis (PLS-DA) is a versatile algorithm that can be
used for predictive and descriptive modelling as well as for discriminative variable selection …

Cross-validation using randomized subsets of data—known as k-fold cross-validation—is a
powerful means of testing the success rate of models used for classification. However, few if …

Establishing brain-behavior associations that map brain organization to phenotypic
measures and generalize to novel individuals remains a challenge in neuroimaging …

The imprecise nature of psychiatric nosology restricts progress towards characterizing and
treating mental health disorders. One issue is the 'heterogeneity problem': different causal …

Decoding, ie prediction from brain images or signals, calls for empirical evaluation of its
predictive power. Such evaluation is achieved via cross-validation, a method also used to …

Several lines of evidence support the link between maternal inflammation during pregnancy
and increased likelihood of neurodevelopmental and psychiatric disorders in offspring. This …

Defect prediction models help software quality assurance teams to allocate their limited
resources to the most defect-prone modules. Model validation techniques, such as-fold …

Background We address the problem of selecting and assessing classification and
regression models using cross-validation. Current state-of-the-art methods can yield models …

Fabric defect detection is a necessary and essential step of quality control in the textile
manufacturing industry. Traditional fabric inspections are usually performed by manual …