Decision Trees Can Initialize Radial-Basis Function Networks  

Oleh:

Kubat, M.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 9 no. 5 (1998), page 813-821.
Topik: radial basis function network; decision trees; radial - basis function; networks

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.3 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

Lihat Detail Induk

Isi artikel

Successful implementations of radial - basis function (RBF) networks for classification tasks must deal with architectural issues, the burden of irrelevant attributes, scaling, and some other problems. This paper addresses these issues by initializing RBF networks with decision trees that define relatively pure regions in the instance space ; each of these regions then determines one basis function. The resulting network is compact, easy to induce, and has favorable classification accuracy.

Opini Anda

Klik untuk menuliskan opini Anda tentang koleksi ini!

Kembali