Ranking and selection of unsupervised learning marketing segmentation
Knowledge-Based Systems
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The concept of similarity between objects has traditionally been taken as the criterion for recognising their membership of a given class. This paper considers how well an object fits into a class by using the concept of adequacy introduced by the LAMDA learning system [6],[9]. The Global Adequacy Degree (GAD) is a function of the object's class membership. An adequacy threshold is associated with a non-informative class (NIC). Objects falling below this threshold value are not considered to belong to any significant class. In this research, the tensions produced by a classification scheme are defined by means of the adequacy of an object in a class. This allows us to analyse the stability orbalance of the scheme. An example is given in the form of the adequacy and the tension of a classification scheme for a group of customers patronising an imaginary shop.