Unsupervised Parameter Validation of Rule mining
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- UMEMURA Kyoji
- Toyohashi University of Tech
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- HIRONAKA Shiori
- Toyohashi University of Tech
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- TAKAMOTO Ayaka
- Toyohashi University of Tech
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- TAKAHASHI Chako
- Yamagata University
Bibliographic Information
- Other Title
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- ルールマイニングにおける教師なしパラメータバリデーション
Abstract
<p>Rule-mining algorithms require specific treatment for the rules wherein their items appear only a few times. Each rule-mining algorithm contains a tuning parameter related to the fewness of the related items. A typical method to determine this type of tuning parameter uses validation data. Since validation data are only available with knowledge of the correct rules, it is difficult to determine the parameter. Observing various histograms of the estimated strength, we find that the histograms should be smooth if the parameter is reasonable. This study proposed an unsupervised method to determine the tuning parameter for rule-mining tasks by the histograms of estimated results varying the parameter without knowledge of the correct rules.</p>
Journal
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- Proceedings of the Annual Conference of JSAI
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Proceedings of the Annual Conference of JSAI JSAI2023 (0), 2F1GS105-2F1GS105, 2023
The Japanese Society for Artificial Intelligence
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Keywords
Details 詳細情報について
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- CRID
- 1390296808221116928
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- ISSN
- 27587347
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- Text Lang
- ja
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- Data Source
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- JaLC
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- Abstract License Flag
- Disallowed