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Managerial Decision Making Using Cluster Analysis Methods
Managerial Decision Making Using Cluster Analysis Methods

Author(s): František Huňka
Subject(s): Economy, Business Economy / Management, Accounting - Business Administration
Published by: ASERS Publishing
Keywords: cluster analysis; object oriented perspective; decision making support
Summary/Abstract: Decision making represents one of the principal management activities whose quality influence to a considerable extends effective functioning of economic units. Decision making support systems are usually conceived as interactive computer systems which help their users in decision making activities. The core of the computer system is composed of knowledge base and inference mechanism. Of course, a real decision making support systems are based on some theory that is utilized both in the inference mechanism and in the knowledge base. This paper use cluster analysis as a theory on which the knowledge base and inference mechanism is designed and implemented. Cluster analysis covers a row of methods for helping to solve classification problems of multidimensional data. In general, knowledge base in this case is created by classifying verified data into groups called clusters. The inference mechanism than compare a similarity of a new unknown object to clusters creating a knowledge base and inference potential properties of this new object. The result of this process is utilised in decision making. Described approach is illustrated on medical data concerning possibilities of cardiovascular disease which can be possibly used for life insurance.

  • Page Range: 8-25
  • Page Count: 18
  • Publication Year: 2011
  • Language: English