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- W2330249510 abstract "The main goal of Knowledge Discovery inDatabases is to find interesting and usable patterns, meaningfulin their domain. Actionable Knowledge Discovery came toexistence as a direct respond to the need of finding more usablepatterns called actionable patterns. Traditional data miningand algorithms are often confined to deliver frequent patternsand come short for suggesting how to make these patternsactionable. In this scenario the users are expected to act.However, the users are not advised about what to do withdelivered patterns in order to make them usable. In this paper,we present an automated approach to focus on not only creatingrules but also making the discovered rules actionable.Up to now few works have been reported in this field whichlacking incomprehensibility to the user, overlooking the costand not providing rule generality. Here we attempt to present amethod to resolving these issues. In this paper CEARDMmethod is proposed to discover cost-effective action rules fromdata. These rules offer some cost-effective changes totransferring low profitable instances to higher profitable ones.We also propose an idea for improving in CEARDM method." @default.
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- W2330249510 date "2011-01-01" @default.
- W2330249510 modified "2023-10-18" @default.
- W2330249510 title "Robust and Cost-Effective Approach for Discovering Action Rules" @default.
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- W2330249510 doi "https://doi.org/10.7763/ijmlc.2011.v1.48" @default.
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