Thumbnail
Access Restriction
Open

Author Frolov, Alexander A. ♦ Abraham, Ajith ♦ Polyakov, Pavel Y.
Source CiteSeerX
Content type Text
File Format PDF
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Information Gain ♦ Boolean Matrix Factorization ♦ Expectation Maximization Boolean Factor Analysis ♦ Bmf Method ♦ Bar Problem ♦ Dimension Reduction ♦ Second One ♦ Mushroom Dataset ♦ Index Term Dimension Reduction ♦ Bmdp Statistical Software Package ♦ Reconstruction Ability ♦ Computed Factor ♦ Boolean Factor Analysis ♦ First One ♦ Binarization Step ♦ General Remark ♦ M8 Method ♦ Data Mining ♦ Abstract Studied ♦ Data Dimension Reduction
Abstract Abstract—Studied are differences of two approaches to binary data dimension reduction. The first one is Boolean Matrix Factorization and the second one is Expectation Maximization Boolean Factor Analysis. The two BMF methods are used for comparison. First is M8 method from the BMDP statistical software package. The second is the BMF method, as suggested by Belohlavek and Vychodil (BVA2). These two are compared to Expectation Maximization Boolean Factor Analysis extended with binarization step developed here. Generated (Bars problem) and mushroom dataset are used for(experiments. In particular, under scrutiny was the reconstruction ability of the computed factors and the information gain as the measure of dimension reduction. In addition, presented are some general remarks on all the methods being compared. Index Terms—Dimension reduction, statistics, data mining, Boolean factor analysis, Boolean matrix factorization, information gain, likelihood-maximization, bars problem.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study