Constructive Feedforward ART Clustering Networks - Part II  

Oleh:

Baraldi, A. ; Alpaydin, E.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 13 no. 3 (2002), page 662-677.
Topik: networks; ART; clustering networks

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.6 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

For pt. I see ibid., p. 645 - 61 (2002). Part I of this paper defines the class of constructive unsupervised on - line learning simplified adaptive resonance theory (SART) clustering networks. Proposed instances of class SART are the symmetric fuzzy ART (S - Fuzzy ART) and the Gaussian ART (GART) network. In Part II of our work, a third network belonging to class SART, termed fully self - organizing SART (FOSART), is presented and discussed. FOSART is a constructive, soft - to - hard competitive, topology - preserving, minimum - distance - to - means clustering algorithm capable of : 1) generating processing units and lateral connections on an example - driven basis and 2) removing processing units and lateral connections on a minibatch basis. FOSART is compared with Fuzzy ART, S - Fuzzy ART, GART and other well-known clustering techniques (e. g., neural gas and self - organizing map) in several unsupervised learning tasks, such as vector quantization, perceptual grouping and 3 - D surface reconstruction. These experiments prove that when compared with other unsupervised learning networks, FOSART provides an interesting balance between easy user interaction, performance accuracy, efficiency, robustness, and flexibility.

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