Back from experimentation : A study of learning bias in LEGAL - E
نویسندگان
چکیده
This paper studies the computational complexity of the similarity based learning system LEGAL-E. LEGAL-E uses learning parameters to build a join-semi-lattice that characterizes a concept materialized by a set of instances described with binary attributes. LEGAL-E was successfully applied to real problems in diierent domains. However dif-culties remain in the choice of learning parameters. This paper addresses this issue by proposing possible best values for such parameters.
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