Avoiding Pitfalls in Neural Network Research  

Oleh:

Zhang, G.P.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Systems, Man, and Cybernetics: Part C Applications and Reviews vol. 37 no. 1 (Jan. 2007), page 3-16.
Topik: Data; Model Building; Model Evaluation; Neural Networks; Pitfalls; Publication Bias; Software

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II69.1 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

Artificial neural networks (ANNs) have gained extensive popularity in recent years. Research activities are considerable, and the literature is growing. Yet, there is a large amount of concern on the appropriate use of neural networks in published research. The purposes of this paper are to: 1) point out common pitfalls and misuses in the neural network research; 2) draw attention to relevant literature on important issues; and 3) suggest possible remedies and guidelines for practical applications. The main message we aim to deliver is that great care must be taken in using ANNs for research and data analysis.

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