Dual vigilance fuzzy adaptive resonance theory.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 30388429.
- Also identified by DOI 10.1016/j.neunet.2018.09.015.
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Abstract
Clusters retrieved by generic Adaptive Resonance Theory (ART) networks are limited to their internal categorical representation. This study extends the capabilities of ART by incorporating multiple vigilance thresholds in a single network: stricter (data compression) and looser (cluster similarity) vigilance values are used to obtain a many-to-one mapping of categories-to-clusters. It demonstrates this idea in the context of Fuzzy ART, presented as Dual Vigilance Fuzzy ART (DVFA), to improve the ability to capture clusters with arbitrary geometry. DVFA outperformed Fuzzy ART for the datasets in our experiments while yielding a statistically-comparable performance to another more complex, multi-prototype Fuzzy ART-based architecture.
Medical subject headings
- Artificial Intelligence
- Fuzzy Logic