Title of article
Analysis of data complexity measures for classification
Author/Authors
Cano، نويسنده , , José-Ramَn، نويسنده ,
Issue Information
روزنامه با شماره پیاپی سال 2013
Pages
12
From page
4820
To page
4831
Abstract
The study of data complexity metrics is an emergent area in the field of data mining and is focused on the analysis of several data set characteristics to extract knowledge from them. This information can be used to support the election of the proper classification algorithm.
aper addresses the analysis of the relationship between data complexity measures and classifiers behavior. Each one of the metrics is evaluated covering its range of values and studying the classifiers accuracy on these values.
sults offer information about the usefullness of these measures, and which of them allow us to analyze the nature of the input data set and help us to decide which classification method could be the most promising one.
Keywords
data complexity , Class overlapping , Classification , Class separability
Journal title
Expert Systems with Applications
Serial Year
2013
Journal title
Expert Systems with Applications
Record number
2353718
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