Identifying Corporate Performance Factors Based on Feature Selection in Statistical Pattern Recognition: Methods, Application, Interpretation
Identifying Corporate Performance Factors Based on Feature Selection in Statistical Pattern Recognition: Methods, Application, Interpretation

Author(s): Pavel Pudil, Ladislav Blažek, Ondřej Částek, Petr Somol, Jana Pokorná, Maria Králová
Contributor(s): Milan Boháček (Translator)
Subject(s): Social Sciences, Economy, Business Economy / Management, Micro-Economics, Sociology, Methodology and research technology, Accounting - Business Administration
Published by: Masarykova univerzita nakladatelství
Keywords: pattern recognition; competitiveness factors; financial performance; methodology; feature selection; statistics;
Summary/Abstract: This publication summarizes and extends methodology of feature selection (FS) and pattern recognition in search for competitiveness factors and methodology of corporate financial performance (CFP) measurement. Several methods were evaluated and Dependency-Aware Feature Ranking combined with non-linear regression model were applied. Also, this publication suggests and verifies methodology of interpretation results of the FS methods. For start was employed multidimensional linear regression, succeeded by clustering companies according to the factors identified by FS into homogenous groups, dividing them into quartiles based on their CFP and identifying similar values of the factors. This way was captured the non-linearity in the data.

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