Improved Model for Attribute Selection on High-Dimensional Economic Data

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14560%2F14%3A00073551" target="_blank" >RIV/00216224:14560/14:00073551 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/61384399:31160/14:00044170

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Improved Model for Attribute Selection on High-Dimensional Economic Data

Popis výsledku v původním jazyce

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

Název v anglickém jazyce

Improved Model for Attribute Selection on High-Dimensional Economic Data

Popis výsledku anglicky

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

Druh

D - Stať ve sborníku

CEP obor

AE - Řízení, správa a administrativa

OECD FORD obor

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Projekt

<a href="/cs/project/GAP403%2F12%2F1557" target="_blank" >GAP403/12/1557: Přístupy k identifikaci faktorů výkonnosti podniků s důrazem na metody výběru příznaků ve statistickém rozpoznávání.</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2014

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the 2nd International Conference on Management, Leadership and Governance ICMLG 2014

ISBN

9781909507999

ISSN

2049-6818

e-ISSN

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Počet stran výsledku

10

Strana od-do

276-285

Název nakladatele

Academic Publishing International Limited

Místo vydání

Reading (UK)

Místo konání akce

Wellesley

Datum konání akce

1. 1. 2014

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000340523100036