Feature Subset Selection Algorithm for High-Dimensional Data by using FAST Clustering Approach

作者: Raja. K , Kumaravel.

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参考文章(29)
Jerffeson Teixeira De Souza, Feature selection with a general hybrid algorithm University of Ottawa (Canada). ,(2004) , 10.20381/RUOR-19633
Manoranjan Dash, Huan Liu, Hiroshi Motoda, Consistency Based Feature Selection pacific asia conference on knowledge discovery and data mining. pp. 98- 109 ,(2000) , 10.1007/3-540-45571-X_12
Marko Robnik-Šikonja, Igor Kononenko, Theoretical and Empirical Analysis of ReliefF and RReliefF Machine Learning. ,vol. 53, pp. 23- 69 ,(2003) , 10.1023/A:1025667309714
Andrew Y. Ng, On Feature Selection: Learning with Exponentially Many Irrelevant Features as Training Examples international conference on machine learning. pp. 404- 412 ,(1998)
Mark Andrew Hall, Correlation-based Feature Selection for Discrete and Numeric Class Machine Learning international conference on machine learning. pp. 359- 366 ,(2000)
Sanmay Das, Filters, Wrappers and a Boosting-Based Hybrid for Feature Selection international conference on machine learning. pp. 74- 81 ,(2001)
Eric P. Xing, Richard M. Karp, Michael I. Jordan, Feature selection for high-dimensional genomic microarray data international conference on machine learning. pp. 601- 608 ,(2001)
Pat Langley, Selection of Relevant Features in Machine Learning national conference on artificial intelligence. pp. 1- 5 ,(1994) , 10.21236/ADA292575
George H John, Ron Kohavi, Karl Pfleger, None, Irrelevant Features and the Subset Selection Problem Machine Learning Proceedings 1994. pp. 121- 129 ,(1994) , 10.1016/B978-1-55860-335-6.50023-4
Huan Liu, Lei Yu, Feature selection for high-dimensional data: a fast correlation-based filter solution international conference on machine learning. pp. 856- 863 ,(2003)