تقرير
Model Based Co-clustering of Mixed Numerical and Binary Data
| العنوان: | Model Based Co-clustering of Mixed Numerical and Binary Data |
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| المؤلفون: | Bouchareb, Aichetou, Boullé, Marc, Clérot, Fabrice, Rossi, Fabrice |
| المصدر: | Advances in Knowledge Discovery and Management, 834, Springer International Publishing, pp.3-22, 2019, Studies in Computational Intelligence |
| سنة النشر: | 2022 |
| المجموعة: | Computer Science Mathematics Statistics |
| مصطلحات موضوعية: | Computer Science - Machine Learning, Mathematics - Statistics Theory, Statistics - Machine Learning |
| الوصف: | Co-clustering is a data mining technique used to extract the underlying block structure between the rows and columns of a data matrix. Many approaches have been studied and have shown their capacity to extract such structures in continuous, binary or contingency tables. However, very little work has been done to perform co-clustering on mixed type data. In this article, we extend the latent block models based co-clustering to the case of mixed data (continuous and binary variables). We then evaluate the effectiveness of the proposed approach on simulated data and we discuss its advantages and potential limits. |
| نوع الوثيقة: | Working Paper |
| DOI: | 10.1007/978-3-030-18129-1_1 |
| URL الوصول: | http://arxiv.org/abs/2212.11725 |
| رقم الأكسشن: | edsarx.2212.11725 |
| قاعدة البيانات: | arXiv |
| DOI: | 10.1007/978-3-030-18129-1_1 |
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