Improved Model for Attribute Selection on High-Dimensional
Economic Data

D 2014

Improved Model for Attribute Selection on High-Dimensional Economic Data

SOMOL, Petr; Pavel PUDIL; Ondřej ČÁSTEK a Jana POKORNÁ

Základní údaje

Originální název

Improved Model for Attribute Selection on High-Dimensional Economic Data

Autoři

SOMOL, Petr; Pavel PUDIL; Ondřej ČÁSTEK a Jana POKORNÁ

Vydání

1. vyd. Reading (UK), Proceedings of the 2nd International Conference on Management, Leadership and Governance ICMLG 2014, od s. 276-285, 10 s. 2014

Nakladatel

Academic Publishing International Limited

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

50600 5.6 Political science

Stát vydavatele

Velká Británie a Severní Irsko

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

tištěná verze "print"

Označené pro přenos do RIV

Ano

Kód RIV

RIV/00216224:14560/14:00073551

Organizační jednotka

Ekonomicko-správní fakulta

ISBN

978-1-909507-99-9

ISSN

UT WoS

000340523100036

Klíčová slova anglicky

Corporate Competitiveness; Financial Performance; Non-linear Regression; Feature Selection; Statistical Pattern Recognition

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 23. 5. 2017 12:47, doc. Ing. Ondřej Částek, Ph.D.

Anotace

V originále

This paper represents a continuation of our previous results, which were closely linked to the topic of automated search for factors of corporate competitiveness. The main goal remains to demonstrate a significant mutual dependency between corporate competitiveness (characterized mainly by their financial performance) and a group of selected characteristics describing these companies. Such characteristics can be regarded as competitiveness factors. Characteristics are generally not mutually independent, thus factors have to be selected in multidimensional space. Compared to our previous work presented at ICMLG 2013 in Bangkok, we analyse here a more precise and larger dataset of enterprises from the Czech Republic and, moreover, with a higher dimensionality (with more variables or features). This paper presents both the new improved algorithms for using the regression model in the search for key factors of corporate competitiveness and also new results achieved with this larger dataset.

Návaznosti

GAP403/12/1557, projekt VaV

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

Citovat

SOMOL, Petr; Pavel PUDIL; Ondřej ČÁSTEK a Jana POKORNÁ. Improved Model for Attribute Selection on High-Dimensional Economic Data. In Dr Phil Dover, Dr Sam Hariharan and Dr. Michael Cummings. Proceedings of the 2nd International Conference on Management, Leadership and Governance ICMLG 2014. 1. vyd. Reading (UK): Academic Publishing International Limited, 2014, s. 276-285. ISBN 978-1-909507-99-9.

@inproceedings{1173481,
   author = {Somol, Petr and Pudil, Pavel and Částek, Ondřej and Pokorná, Jana},
   address = {Reading (UK)},
   booktitle = {Proceedings of the 2nd International Conference on Management, Leadership and Governance ICMLG 2014},
   edition = {1.},
   editor = {Dr Phil Dover, Dr Sam Hariharan and Dr. Michael Cummings},
   keywords = {Corporate Competitiveness; Financial Performance; Non-linear Regression; Feature Selection; Statistical Pattern Recognition},
   howpublished = {tištěná verze "print"},
   language = {eng},
   location = {Reading (UK)},
   isbn = {978-1-909507-99-9},
   pages = {276-285},
   publisher = {Academic Publishing International Limited},
   title = {Improved Model for Attribute Selection on High-Dimensional Economic Data},
   year = {2014}
}

TY  - CONF
ID  - 1173481
AU  - Somol, Petr - Pudil, Pavel - Částek, Ondřej - Pokorná, Jana
PY  - 2014
TI  - Improved Model for Attribute Selection on High-Dimensional Economic Data
PB  - Academic Publishing International Limited
CY  - Reading (UK)
SN  - 9781909507999
KW  - Corporate Competitiveness
KW  - Financial Performance
KW  - Non-linear Regression
KW  - Feature Selection
KW  - Statistical Pattern Recognition
N2  - This paper represents a continuation of our previous results, which were closely linked to the topic of automated search for factors of corporate competitiveness. The main goal remains to demonstrate a significant mutual dependency between corporate competitiveness (characterized mainly by their financial performance) and a group of selected characteristics describing these companies. Such characteristics can be regarded as competitiveness factors. Characteristics are generally not mutually independent, thus factors have to be selected in multidimensional space. Compared to our previous work presented at ICMLG 2013 in Bangkok, we analyse here a more precise and larger dataset of enterprises from the Czech Republic and, moreover, with a higher dimensionality (with more variables or features). This paper presents both the new improved algorithms for using the regression model in the search for key factors of corporate competitiveness and also new results achieved with this larger dataset.
ER  -

SOMOL, Petr; Pavel PUDIL; Ondřej ČÁSTEK a Jana POKORNÁ. Improved Model for Attribute Selection on High-Dimensional Economic Data. In Dr Phil Dover, Dr Sam Hariharan and Dr. Michael Cummings. \textit{Proceedings of the 2nd International Conference on Management, Leadership and Governance ICMLG 2014}. 1. vyd. Reading (UK): Academic Publishing International Limited, 2014, s.~276-285. ISBN~978-1-909507-99-9.

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