'Action rules' diaporamas de présentation

ACTION RULES & META ACTIONS

www.kdd.uncc.edu. ACTION RULES & META ACTIONS. College of Computing and Informatics University of North Carolina, Charlotte. presented by Zbigniew W. Ras University of North Carolina, Charlotte, NC College of Computing and Informatics. Introduction : Action Rule.

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CLIRS: Customer Loyalty Improvement Recommender System .

CLIRS: Customer Loyalty Improvement Recommender System. Built for the Daniel Group. (2013-2018). presented by Zbigniew W. Ras. Research sponsored by. Project Team. KDD Lab Members. Kasia Tarnowska (San Jose State University). Pauline Brunet (Paris Tech., France ). Jieyan Kuang

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Action Rules Discovery without pre-existing classification rules

Action Rules Discovery without pre-existing classification rules. B y Zbigniew W. Ras 1,2 and Agnieszka Dardzinska 1,3 University of North Carolina, Charlotte, NC, USA Polish Academy of Science, Warsaw, Poland Bialystok Technical University, Bialystok, Poland.

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ACTION RULES

ACTION RULES. Slides by A A Tzacheva. Knowledge Discovery. The nontrivial process of identifying valid , novel, potentially useful, and ultimately understandable patterns in data. (Fayyad, et al 1996).

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ACTION RULES /Lecture II/

ACTION RULES /Lecture II/. presented by Zbigniew Ras UNC-Charlotte, Computer Science. Action Rules [Z. Ras & A. Wieczorkowska]. Decision table. Any information system of the form S = (U, A Fl ? A St ? {d}), where d ? A Fl ? A St is a distinguished attribute called decision.

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Action Rules (AR)

Action Rules (AR). Early Implementation methods Complex abstract machines (e.g., CHIP) Special purpose constructs Indexicals, delay constructs, attribute variables General purpose language (CHR) Motivation of AR

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Constraints & Triggers

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