Open AccessAn iterative feature selection procedure for a classification problem based on the method of logical analysis of data
Author(s) -
Roman Kuzmich,
Alena Stupina,
I S Zhirnova,
O V Slinitsyna,
Ivan Boubriak
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2094/3/032054
Subject(s) - selection (genetic algorithm) , computer science , feature selection , logical analysis , iterative method , ranking (information retrieval) , data mining , feature (linguistics) , pattern recognition (psychology) , artificial intelligence , logical data model , logical conjunction , algorithm , machine learning , mathematics , data modeling , statistics , mathematical statistics , linguistics , philosophy , programming language , database
An iterative procedure for selecting features for classifying observations is proposed. The main principles of the proposed iterative procedure are ranking and selection of features according to the frequency of their use when constructing logical patterns based on the method of logical analysis of data. The empirical confirmation of the expediency of this procedure is given.