Constructive algorithms for structure learning in feedforward neural networks for regression problems

  • Authors:
  • Tin-Yau Kwok;Dit-Yan Yeung

  • Affiliations:
  • Dept. of Comput. Sci., Hong Kong Univ. of Sci. & Technol., Kowloon;-

  • Venue:
  • IEEE Transactions on Neural Networks
  • Year:
  • 1997

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Abstract

In this survey paper, we review the constructive algorithms for structure learning in feedforward neural networks for regression problems. The basic idea is to start with a small network, then add hidden units and weights incrementally until a satisfactory solution is found. By formulating the whole problem as a state-space search, we first describe the general issues in constructive algorithms, with special emphasis on the search strategy. A taxonomy, based on the differences in the state transition mapping, the training algorithm, and the network architecture, is then presented