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      Concept representation with overlapping feature intervals

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      Author(s)
      Güvenir, H. A.
      Koç, H. G.
      Date
      1998
      Source Title
      Cybernetics and Systems
      Print ISSN
      0196-9722
      Electronic ISSN
      1087-6553
      Publisher
      Taylor & Francis Inc.
      Volume
      29
      Issue
      3
      Pages
      263 - 282
      Language
      English
      Type
      Article
      Item Usage Stats
      205
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      190
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      Abstract
      This article presents a new form of exemplar-based learning method, based on overlapping feature intervals. In this model, a concept is represented by a collection of overlappling intervals for each feature and class. Classification with Overlapping Feature Intervals (COFI) is a particular implementation of this technique. In this incremental, inductive, and supervised learning method, the basic unit of the representation is an interval. The COFI algorithm learns the projections of the intervals in each feature dimension for each class. Initially, an interval is a point on a feature-class dimension; then it can be expanded through generalization. No specialization of intervals is done on feature-class dimensions by this algorithm. Classification in the COFI algorithm is based on a majority voting among the local predictions that are made individually by each feature. An evaluation of COFI and its comparison with similar other classification techniques is given.
      Keywords
      Learning Algorithms
      Learning Systems
      Classification with Overlapping Feature Intervals (COFI) Algorithm
      Cybernetics
      Permalink
      http://hdl.handle.net/11693/25312
      Published Version (Please cite this version)
      https://doi.org/10.1080/019697298125713
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      • Department of Computer Engineering 1561
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