A new pre-processing method for regression

  • Authors:

  • Wen-Feng Jing;De-Yu Meng;Ming-Wei Dai;Zongben Xu

  • Affiliations:

  • Institute for Information and System Science, Xi’an Jiaotong University, Xi’an, China;Institute for Information and System Science, Xi’an Jiaotong University, Xi’an, China;Institute for Information and System Science, Xi’an Jiaotong University, Xi’an, China;Institute for Information and System Science, Xi’an Jiaotong University, Xi’an, China

  • Venue:
  • ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
  • Year:
  • 2006

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Abstract

A new pre-processing method for regression is developed. The core idea is using three rules to clarify regression raw data. The rules are realized through introducing a judge function on the regression datum whose value determines the importance of the datum. By applying the rules, a new pre-processing method for regression is developed. Performance of the new method on a series of simulations demonstrate that it not only significantly increases computational efficiency and robustness, but also preserves generalization capability of a regression method. Incorporated with any regression method, the developed method then can be efficiently applied to regression of large data sets.