lippolt@dnlunx.UUCP (Ben Lippolt) (09/08/88)
To: mcvax!cwi.nl!comp-ai-digest@uunet.UU.NET Path: dnlunx!lippolt From: Ben Lippolt <mcvax!dnlunx!lippolt@uunet.UU.NET> Newsgroups: comp.ai,comp.ai.digest Subject: Should we use an inductive tool for this problem? Keywords: inductive reasoning tools Date: Mon, 5 Sep 88 10:48 EDT Organization: Dr. Neher Labs, (Netherlands PTT) Lines: 47 Hello, We have the following problem: We have about 200 items. Each item belongs to one of 13 classes and is described by 12 attributes. The values an item has for these 12 attributes are not absolute, however, but are expressed relative to the other items. Like this: attr1 attr2 attr3 attr4 3 2 4 3 2 3 3 4 1 4 2 2 4 1 1 1 The numbers refer to items 1 to 4. Let's say that item 1 belongs to class 1, item 2 to class 3, item 3 to class 6 and item 4 to class 3. There is a correlation between the class an item belongs to and the positions it has for each attribute. We can see, for instance, that item 3 is ranked above item 1 for all attributes and that the class of item 3 is higher than the class of item 1. If we look at items 2 and 4, we see that of these two for some attributes item 2 is ranked higher and for some attributes item 4. Both items belong to the same class. What we want to do now, is to check the consistency of the correlation between the class an item belongs to and the relative positions it occupies for the twelve attributes. For instance, an item that is ranked very high for each attribute should not belong to the same class as an item that is ranked very low for each attribute. We want to start with e.g. 50 items and check for each new item that we add whether its class and positions are consistent with the other items. Our questions are: Can we use an inductive tool for this problem? Are 50 cases, with 12 attributes each, enough to start working with? Can we find inconsistencies, which might be rather vague, with such a tool? Is it possible to incorporate fuzzy logic in an inductive tool? Which tool should we use? Any comments are highly appreciated. Ben Lippolt (..!mcvax!dnlunx!lippolt, or lippolt@hlsdnl5) Marlies van Steenbergen (..!mcvax!dnlunx!marlies) PTT Research, Neher Laboratories.