A Recurrent Neural Network based Clustering Method for Binary Data Sets in Education

• URL: http://arxiv.org/abs/2508.13224v1
• Date: Sun, 17 Aug 2025 13:26:43 GMT
• Title: A Recurrent Neural Network based Clustering Method for Binary Data Sets in Education
• Authors: Mizuki Ohira, Toshimichi Saito,
• Abstract summary: As the number of students increases, the S-P chart becomes hard to handle.<n>We present a simple clustering method based on the network dynamics.<n>In the method, the network has multiple fixed points and basins of attraction give singularity clusters corresponding to small S-P charts.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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