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@book{1218727,
author = {Pudil, Pavel and Blažek, Ladislav and Částek, Ondřej and Somol, Petr and Pokorná, Jana and Králová, Maria},
address = {Brno},
doi = {http://dx.doi.org/10.5817/CZ.MUNI.M210-7557-2014},
edition = {1.},
keywords = {Dependency-Aware Feature Ranking; Feature Selection; Pattern Recognition; Corporate Financial Performance; Competitiveness; Factors; Linear Regression; Non-linear Regression; Sequential Forward Flow Search; k Nearest Neighbours},
howpublished = {tištěná verze "print"},
language = {eng},
location = {Brno},
isbn = {978-80-210-7557-3},
publisher = {Masarykova univerzita},
title = {Identifying Corporate Performance Factors Based on Feature Selection in Statistical Pattern Recognition: METHODS, APPLICATION, INTERPRETATION},
year = {2014}
}
TY - BOOK
ID - 1218727
AU - Pudil, Pavel - Blažek, Ladislav - Částek, Ondřej - Somol, Petr - Pokorná, Jana - Králová, Maria
PY - 2014
TI - Identifying Corporate Performance Factors Based on Feature Selection in Statistical Pattern Recognition: METHODS, APPLICATION, INTERPRETATION
VL - Neuveden
PB - Masarykova univerzita
CY - Brno
SN - 9788021075573
KW - Dependency-Aware Feature Ranking
KW - Feature Selection
KW - Pattern Recognition
KW - Corporate Financial Performance
KW - Competitiveness
KW - Factors
KW - Linear Regression
KW - Non-linear Regression
KW - Sequential Forward Flow Search
KW - k Nearest Neighbours
N2 - 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.
ER -
PUDIL, Pavel, Ladislav BLAŽEK, Ondřej ČÁSTEK, Petr SOMOL, Jana POKORNÁ and Maria KRÁLOVÁ. \textit{Identifying Corporate Performance Factors Based on Feature Selection in Statistical Pattern Recognition: METHODS, APPLICATION, INTERPRETATION}. 1st ed. Brno: Masarykova univerzita, 2014, 170 pp. ISBN~978-80-210-7557-3. Available from: https://dx.doi.org/10.5817/CZ.MUNI.M210-7557-2014.
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