Modified ART 2A Growing Network Capable of Generating A Fixed Number of Nodes  

Oleh:

He, Ji ; Tan, Ah-Hwee ; Tan, Chew-Lim

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 15 no. 3 (May 2004), page 728-737.
Topik: networks; modified; ART 2A; growing; network capable; fixed number of node

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.10 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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This paper introduces the Adaptive Resonance Theory under Constraint (ART - C 2A) learning paradigm based on ART 2A, which is capable of generating a user - defined number of recognition nodes through online estimation of an appropriate vigilance threshold. Empirical experiments compare the cluster validity and the learning efficiency of ART - C 2A with those of ART 2A, as well as three closely related clustering methods, namely online K - Means, batch K - Means, and SOM, in a quantitative manner. Besides retaining the online cluster creation capability of ART 2A, ART - C 2A gives the alternative clustering solution, which allows a direct control on the number of output clusters generated by the self - organizing process.

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