A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf
.
Revisiting evolutionary algorithms in feature selection and nonfuzzy/fuzzy rule based classification
2013
Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery
This paper discusses the relevance and possible applications of evolutionary algorithms, particularly genetic algorithms, in the domain of knowledge discovery in databases. Knowledge discovery in databases is a process of discovering knowledge along with its validity, novelty, and potentiality. Various genetic-based feature selection algorithms with their pros and cons are discussed in this article. Rule (a kind of high-level representation of knowledge) discovery from databases, posed as
doi:10.1002/widm.1087
fatcat:j3evku467fbifgrkt5fpu5x4im