تقرير
Pre-Sorted Tsetlin Machine (The Genetic K-Medoid Method)
| العنوان: | Pre-Sorted Tsetlin Machine (The Genetic K-Medoid Method) |
|---|---|
| المؤلفون: | Morris, Jordan |
| سنة النشر: | 2024 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Neural and Evolutionary Computing, Computer Science - Artificial Intelligence, Computer Science - Machine Learning, B.6.0, B.7.0, C.1.0, I.2.6 |
| الوصف: | This paper proposes a machine learning pre-sort stage to traditional supervised learning using Tsetlin Machines. Initially, K data-points are identified from the dataset using an expedited genetic algorithm to solve the maximum dispersion problem. These are then used as the initial placement to run the K-Medoid clustering algorithm. Finally, an expedited genetic algorithm is used to align K independent Tsetlin Machines by maximising hamming distance. For MNIST level classification problems, results demonstrate up to 10% improvement in accuracy, approx. 383X reduction in training time and approx. 86X reduction in inference time. Comment: 6 pages, 12 figures, 3 tables |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2403.09680 |
| رقم الأكسشن: | edsarx.2403.09680 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |