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Updated: Jun 15, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
Published on: October 11, 2018
Strategy selection and use during classification skill acquisition
Lyle E Bourne1, William D Raymond, Alice F Healy
1Department of Psychology and Neuroscience, University of Colorado, Boulder, CO 80309-0345, USA. Lyle.Bourne@Colorado.edu
Abstract:
Two experiments examined 3 variables affecting accuracy, response time, and reports of strategy use in a binary classification skill task. In Experiment 1, higher rule cue salience, allowing faster rule application, produced higher aggregate rule use than lower rule cue salience. After participants were pretrained on the relevant classification rule, rule reports were high but generally declined across training trials; after participants were pretrained on an irrelevant rule, reports of the relevant rule increased across training trials. In Experiment 2, no rule pretraining produced a pattern of results like that obtained with irrelevant rule pretraining in Experiment 1. Presenting novel stimuli during training in Experiment 2 elevated aggregate rule reports relative to conditions where they were absent. Two participant subgroups were identified: those persisting in rule reports and those transitioning from rule to memory reports during training. The proportion of persistent rule users was higher after rule discovery than after relevant rule pretraining. Overall, the results indicate that differences among prior experiments can be reconciled. Further, they raise questions about the inevitability of memory-based automaticity in binary classification, favoring instead strategy choice based on the costs and benefits of a particular strategy and of a shift from one strategy to another.
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