Multivariate classification of neuroimaging data with nested subclasses: Biased accuracy and implications for hypothesis testing
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DOI: 10.1371/journal.pcbi.1006486
Abstract: Biological data sets are typically characterized by high dimensionality and low effect sizes. A powerful method for detecting systematic differences between experimental conditions in such multivariate data sets is multivariate pattern analysis (MVPA), particularly pattern… read more here.
Keywords: classification; classification neuroimaging; subclass bias; subclass ... See more keywords