Identifying Corporate Performance Factors Based on Feature
Selection in Statistical Pattern Recognition: METHODS,
APPLICATION, INTERPRETATION

B 2014

Identifying Corporate Performance Factors Based on Feature Selection in Statistical Pattern Recognition: METHODS, APPLICATION, INTERPRETATION

PUDIL, Pavel, Ladislav BLAŽEK, Ondřej ČÁSTEK, Petr SOMOL, Jana POKORNÁ et. al.

Basic information

Original name

Identifying Corporate Performance Factors Based on Feature Selection in Statistical Pattern Recognition: METHODS, APPLICATION, INTERPRETATION

Authors

PUDIL, Pavel (203 Czech Republic), Ladislav BLAŽEK (203 Czech Republic, guarantor, belonging to the institution), Ondřej ČÁSTEK (203 Czech Republic, belonging to the institution), Petr SOMOL (203 Czech Republic), Jana POKORNÁ (203 Czech Republic, belonging to the institution) and Maria KRÁLOVÁ (203 Czech Republic, belonging to the institution)

Edition

1. vyd. Brno, 170 pp. 2014

Publisher

Masarykova univerzita

Other information

Language

English

Type of outcome

Odborná kniha

Field of Study

50600 5.6 Political science

Country of publisher

Czech Republic

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

printed version "print"

RIV identification code

RIV/00216224:14560/14:00074365

Organization unit

Faculty of Economics and Administration

ISBN

978-80-210-7557-3

DOI

http://dx.doi.org/10.5817/CZ.MUNI.M210-7557-2014

Keywords in English

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

Abstract

V originále

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.

Links

GAP403/12/1557, research and development project

Name: Přístupy k identifikaci faktorů výkonnosti podniků s důrazem na metody výběru příznaků ve statistickém rozpoznávání.

Files attached

monografie.pdf

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Citovat

PUDIL, Pavel, Ladislav BLAŽEK, Ondřej ČÁSTEK, Petr SOMOL, Jana POKORNÁ and Maria KRÁLOVÁ. 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.

@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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