High-efficiency SVM active half-supervision learning algorithm
A semi-supervised learning and active learning technology, applied in computing, computer components, instruments, etc., can solve problems such as lack of incremental learning ability, affecting active learning performance, and high complexity
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
Method used
Image
Examples
Example Embodiment
[0107] SVM active learning generally selects the most uncertain and low-confidence samples of the current learner for labeling, and relatively certain or well-represented samples are not used for training, while semi-supervised learning methods can use these classifiers to label them Relatively certain or high-confidence samples to make more full use of the information contained in unlabeled samples that are useful for classifier training, which can avoid the error propagation caused by the uncertainty of the initial classifier in SVM active learning, thereby improving SVM Active Learning Performance. Based on this, the present invention provides an SVM active semi-supervised learning algorithm that integrates semi-supervised learning and active learning. figure 1 , the process of the efficient SVM active semi-supervised learning algorithm of the present invention is introduced in detail.
[0108] In this example, the data uses the breast-cancer-wisconsin, ionosphere, house-vot...
PUM
Abstract
Description
Claims
Application Information
- R&D Engineer
- R&D Manager
- IP Professional
- Industry Leading Data Capabilities
- Powerful AI technology
- Patent DNA Extraction
Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.
© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap