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http://dx.doi.org/10.6109/jkiice.2010.14.1.053

A Classifier Capable of Handling Incomplete Data Set  

Lee, Jong-Chan (청운대학교 인터넷학과)
Lee, Won-Don (충남대학교 전기정보통신공학부 컴퓨터)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.14, no.1, 2010 , pp. 53-62 More about this Journal
Abstract
This paper introduces a classification algorithm which can be applied to a learning problem with incomplete data sets, missing variable values or a class value. This algorithm uses a data expansion method which utilizes weighted values and probability techniques. It operates by extending a classifier which are considered to be in the optimal projection plane based on Fisher's formula. To do this, some equations are derived from the procedure to be applied to the data expansion. To evaluate the performance of the proposed algorithm, results of different measurements are iteratively compared by choosing one variable in the data set and then modifying the rate of missing and non-missing values in this selected variable. And objective evaluation of data sets can be achieved by comparing, the result of a data set with non-missing variable with that of C4.5 which is a known knowledge acquisition tool in machine learning.
Keywords
FLDF; Missing value; Extended data expression; Optimized projection plane; Entropy function;
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