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Decision algorithms ensure an appropriate extraction of information from datasets by means of decision rules. These algorithms are analyzed by the notion of efficiency, which focuses on the objects correctly classified by using only the most representative decision rules. This paper presents a novel notion of efficiency in the fuzzy framework based on the certainty of the decision rules, in order to quantify the quality of classification of the studied algorithm.

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Efficiency of Fuzzy Decision Algorithms Based on the Certainty of Decision Rules

  • 会议论文

  • 发表日期：

    2025年

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  • Fernando Chacón-Gómez,
  • M. Eugenia Cornejo,
  • Jesús Medina

摘要

Decision algorithms ensure an appropriate extraction of information from datasets by means of decision rules. These algorithms are analyzed by the notion of efficiency, which focuses on the objects correctly classified by using only the most representative decision rules. This paper presents a novel notion of efficiency in the fuzzy framework based on the certainty of the decision rules, in order to quantify the quality of classification of the studied algorithm.