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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2508.13224 |
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| _version_ | 1866913996512165888 |
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| author | Ohira, Mizuki Saito, Toshimichi |
| author_facet | Ohira, Mizuki Saito, Toshimichi |
| contents | This paper studies an application of a recurrent neural network to clustering method for the S-P chart: a binary data set used widely in education. As the number of students increases, the S-P chart becomes hard to handle. In order to classify the large chart into smaller charts, we present a simple clustering method based on the network dynamics. In the method, the network has multiple fixed points and basins of attraction give clusters corresponding to small S-P charts. In order to evaluate the clustering performance, we present an important feature quantity: average caution index that characterizes singularity of students answer oatterns. Performing fundamental experiments, effectiveness of the method is confirmed. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_13224 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Recurrent Neural Network based Clustering Method for Binary Data Sets in Education Ohira, Mizuki Saito, Toshimichi Machine Learning Computers and Society This paper studies an application of a recurrent neural network to clustering method for the S-P chart: a binary data set used widely in education. As the number of students increases, the S-P chart becomes hard to handle. In order to classify the large chart into smaller charts, we present a simple clustering method based on the network dynamics. In the method, the network has multiple fixed points and basins of attraction give clusters corresponding to small S-P charts. In order to evaluate the clustering performance, we present an important feature quantity: average caution index that characterizes singularity of students answer oatterns. Performing fundamental experiments, effectiveness of the method is confirmed. |
| title | A Recurrent Neural Network based Clustering Method for Binary Data Sets in Education |
| topic | Machine Learning Computers and Society |
| url | https://arxiv.org/abs/2508.13224 |