Estimating attributes: analysis and extensions of RELIEF
作者： Igor Kononenko
关键词: Machine learning 、 Context (language use) 、 Artificial intelligence 、 Information gain 、 Minimum redundancy feature selection 、 Data mining 、 Relief algorithm 、 Computer science 、 Quality (business)
摘要: In the context of machine learning from examples this paper deals with problem estimating quality attributes and without dependencies among them. Kira Rendell (1992a,b) developed an algorithm called RELIEF, which was shown to be very efficient in attributes. Original RELIEF can deal discrete continuous is limited only two-class problems. analysed extended noisy, incomplete, multi-class data sets. The extensions are verified on various artificial one well known real-world problem.
springer.com
core.ac.uk
acm.org
sci-hub.se 参考文章(10)
Padhraic Smyth, Rodney M. Goodman, Rule Induction Using Information Theory. Knowledge Discovery in Databases. pp. 159- 176 ,(1991)
Kenji Kira, Larry A. Rendell, The feature selection problem: traditional methods and a new algorithm national conference on artificial intelligence. pp. 129- 134 ,(1992)
Kenji Kira, Larry A. Rendell, A Practical Approach to Feature Selection international conference on machine learning. pp. 249- 256 ,(1992) , 10.1016/B978-1-55860-247-2.50037-1
Richard A Olshen, Charles J Stone, Leo Breiman, Jerome H Friedman, Classification and regression trees ,(1983)
William J Frawley, Christopher J Matheus, Knowledge Discovery in Databases MIT Press. ,(1991)
Igor Kononenko, Semi-naive bayesian classifier Lecture Notes in Computer Science. pp. 206- 219 ,(1991) , 10.1007/BFB0017015
Earl B. Hunt, Philip J. Stone, Janet Marin, Experiments in induction ,(1966)
Pat Langley, Editorial: On Machine Learning Machine Learning. ,vol. 1, pp. 5- 10 ,(1986) , 10.1023/A:1022687019898
J.R. Quinlan, Induction of Decision Trees Machine Learning. ,vol. 1, pp. 81- 106 ,(1986) , 10.1023/A:1022643204877
Methodologies for intelligent systems, 5 Methodologies for Intelligent Systems. pp. 534- 534 ,(1991) , 10.1007/3-540-54563-8