Optimized Bayesian adaptive resonance theory mapping model using a rational quadratic kernel and Bayesian quadratic regularization

Abstract Bayesian adaptive resonance theory (ART) and ARTMAP-based neural network classifier (known as BAM) are widely used and achieve good classification performance when solving the problem of the undefinable number of clusters and diffusion of classes found in other networks based on ART, such a...
Ausführliche Beschreibung

Gespeichert in:
Autor*in:

Yang, Shunkun [verfasserIn]

Li, Hongman

Gou, Xiaodong

Bian, Chong

Shao, Qi

Format:

E-Artikel

Sprache:

Englisch

Erschienen:

2021

Schlagwörter:

Bayesian adaptive resonance theory mapping model

Small sample

Rational quadratic kernel

Bayesian quadratic regularization

Anmerkung:

© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021

Übergeordnetes Werk:

Enthalten in: Applied intelligence - Dordrecht [u.a.] : Springer Science + Business Media B.V, 1991, 52(2021), 7 vom: 11. Okt., Seite 7777-7792

Übergeordnetes Werk:

volume:52 ; year:2021 ; number:7 ; day:11 ; month:10 ; pages:7777-7792

Links:

Volltext

DOI / URN:

10.1007/s10489-021-02883-5

Katalog-ID:

SPR046914773

Nicht das Richtige dabei?

Schreiben Sie uns!