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Data mining using fuzzy decision trees: an exposition from a study of public services strategy in the USA

Beynon, Malcolm James and Kitchener, Martin James 2010. Data mining using fuzzy decision trees: an exposition from a study of public services strategy in the USA. In: Syvajarvi, Antti and Stenvall, Jari eds. Data Mining in Public and Private Sectors: Organizational and Government Applications, Hershey, PA.: IGI Global,

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Abstract

The chapter exposits the strategies employed by the public long-term care systems operated by each U.S. state government. The central technique employed in this investigation is fuzzy decision trees (FDTs), producing a rule-based classification system using the well known soft computing methodology of fuzzy set theory. It is a timely exposition, with the employment of set-theoretic approaches to organizational configurations, including the fuzzy set representation, starting to be discussed. The survey details considered, asked respondents to assign each state system to one of the three ‘orientations to innovation’ contained within Miles and Snows’ (1978) classic typology of organizational strategies. The instigated aggregation of the experts’ opinions adheres to the fact that each long-term care system, like all organizations, is “likely to be part prospector, part defender, and part reactor, reflecting the complexity of organizational strategy”. The use of FDTs in the considered organization research problem is pertinent since the linguistic based fuzzy decision rules constructed, open up the ability to understand the relationship between a state’s attributes and their predicted position in a general strategy domain - the essence of data mining.

Item Type: Book Section
Date Type: Publication
Status: Published
Schools: Business (Including Economics)
Subjects: H Social Sciences > H Social Sciences (General)
J Political Science > JA Political science (General)
J Political Science > JK Political institutions (United States)
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Additional Information: Premier Reference Source
Publisher: IGI Global
ISBN: 9781605669069
Related URLs:
Last Modified: 04 Jun 2017 03:37
URI: http://orca.cf.ac.uk/id/eprint/23748

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