Improving Classifier Generalization Real-Time Machine Learning based Applications /
This book elaborately discusses techniques commonly used to improve generalization performance in classification approaches. The contents highlight methods to improve classification performance in numerous case studies: ranging from datasets of UCI repository to predictive maintenance problems and c...
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| Главные авторы: | , |
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| Соавтор: | |
| Формат: | Электронный ресурс eКнига |
| Язык: | английский |
| Опубликовано: |
Singapore :
Springer Nature Singapore : Imprint: Springer,
2023.
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| Редактирование: | 1st ed. 2023. |
| Серии: | Studies in Computational Intelligence,
989 |
| Предметы: | |
| Online-ссылка: | https://doi.org/10.1007/978-981-19-5073-5 |
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Оглавление:
- Introduction to classification algorithms
- Methods to improve generalization performance
- MVPC – a classifier with very low VC dimension
- Framework for reliable fault detection with sensor data
- Membership functions for Fuzzy Support Vector Machine in noisy environment
- Stacked Denoising Sparse Autoencoder based Fuzzy rule classifiers
- Epilogue.