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Complex networks are explored as powerful tools in machine learning, providing a foundation for techniques in supervised, unsupervised, and semi-supervised learning. The book details a stochastic particle competition method for non-supervised and semi-supervised learning, including an analytical framework for predicting its behavior. It addresses data reliability in semi-supervised contexts, a rarely covered topic. Additionally, a hybrid classification technique is introduced, merging low-level classification with high-level feature extraction from network data, enhancing semantic understanding.
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Machine Learning in Complex Networks, Thiago Christiano Silva, Liang Zhao
- Language
- Released
- 2016
- product-detail.submit-box.info.binding
- (Hardcover)
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- Title
- Machine Learning in Complex Networks
- Language
- English
- Authors
- Thiago Christiano Silva, Liang Zhao
- Publisher
- Springer International Publishing
- Released
- 2016
- Format
- Hardcover
- Pages
- 352
- ISBN13
- 9783319172897
- Category
- Mathematics
- Description
- Complex networks are explored as powerful tools in machine learning, providing a foundation for techniques in supervised, unsupervised, and semi-supervised learning. The book details a stochastic particle competition method for non-supervised and semi-supervised learning, including an analytical framework for predicting its behavior. It addresses data reliability in semi-supervised contexts, a rarely covered topic. Additionally, a hybrid classification technique is introduced, merging low-level classification with high-level feature extraction from network data, enhancing semantic understanding.