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This paper investigates the utility of using aggregate (average, max etc.) information in a multi-sample classification problem in terms of the accuracy of the overall classification, and the prediction of estimated error. Bayesian networks are presented here in order to allow comparison of these results with those of a previously presented fuzzy inference system. Different structures of Bayesian...
A system is presented which is oriented at aiding medical professionals in the diagnosis of neuromuscular disease using a fuzzy rule-based classification system. Visualization of the fuzzy rules, which are contributors to the overall classification, allows the user to determine their level of confidence with the classification of the system. During the development of this system, the choice between...
The linguistic terms of a linguistic variable classify the numeric values of their universe. In that sense, they are categories which are defined over a space of values. In this work a hierarchical model of a linguistic variable is analyzed from the point of view of the principles of categorization and hierarchy theory. It is shown how several partial orders can be defined over the hierarchical model...
In this paper, we derive sufficient conditions under which the single-input single-output fuzzy system is bounded by linear functions in its output. If the fuzzy system is constructed with the complete and consistent fuzzy sets with trapezoid membership functions, we show that the derived conditions are simply the constraints on the consequent part parameters. Then we prove that any continuously differentiable...
The ID3 algorithm forms the basis for many decision trees' algorithms and programs. Trees produced by this algorithm are known to be very sensitive to small changes in attribute values. Fuzzy ID3 is an extension of ID3; it integrates fuzzy set theory and fuzzy logic with ID3. This integration reduces the sensitivity of the produced decision trees to small changes in attribute values, and helps in...
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