Similarity of feature selection methods: An empirical study across data intensive classification tasks. Issue 10 (15th June 2015)

• Record Type: Journal Article
• Authors: Dessì, Nicoletta; Pes, Barbara
• Is Part Of: Expert systems with applications. Volume 42:Issue 10(2015)
• Page Start: 4632
• Page End: 4642
• Publication Date: 2015-06-15
• Subjects: Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2015.01.069
• Languages: English
• ISSNs: 0957-4174

Abstract

<abstract xml:lang="en" abstract-type="author-highlights" id="ab005"> <title id="st085">Highlights</title> <sec> <p id="sp0005"> <list id="l0005"> <list-item id="o0005"> <label></label> <p id="p0315">We empirically investigated the similarity among feature selection methods.</p> </list-item> <list-item id="o0010"> <label></label> <p id="p0320">Extensive experiments were carried out across high dimensional classification tasks.</p> </list-item> <list-item id="o0015"> <label></label> <p id="p0325">We obtained useful insight into the pattern of agreement of eight popular methods.</p> </list-item> </list> </p> </sec> </abstract>