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Marko, R.S. and Lgor, K. (2003) Theoretical and Empirical Analysis of ReliefF and RReliefF. Machine Learning, 53, 23-69.

has been cited by the following article:

• TITLE: Feature Selection for Image Classification Based on a New Ranking Criterion

  AUTHORS: Xuan Zhou, Jiajun Wang

  KEYWORDS: Feature Selection for Image Classification Based on a New Ranking Criterion

  JOURNAL NAME: Journal of Computer and Communications, Vol.3 No.3, March 18, 2015

  ABSTRACT: In this paper, a feature selection method combining the reliefF and SVM-RFE algorithm is proposed. This algorithm integrates the weight vector from the reliefF into SVM-RFE method. In this method, the reliefF filters out many noisy features in the first stage. Then the new ranking criterion based on SVM-RFE method is applied to obtain the final feature subset. The SVM classifier is used to evaluate the final image classification accuracy. Experimental results show that our proposed relief- SVM-RFE algorithm can achieve significant improvements for feature selection in image classification.