Aug 1, 2018 · This paper proposed an active learning-based SVDD method for robust novelty detection. It can reduce the amount of labeled data using an active learning ...
This paper proposed an active learning-based SVDD method for robust novelty detection. It can reduce the amount of labeled data using an active learning ...
Active learning based support vector data description method for robust novelty detection ... description for outlier detection with noise or uncertain data.
Active learning based support vector data description method for robust novelty detection ; 作者： ; 论文关键词：Active learning,SVDD,Robust novelty detection,TEP.
The method consists in combining outlier detection [33][34][35] with uncertainty sampling [5] to select informative samples that are labelled by an oracle and ...
Active Learning Based Support Vector Data Description for Large Data Set Novelty Detection ... Approach for Novelty Detection Using Training Data with Outliers.
The algorithm is a natural extension of the support vector algorithm to the case of unlabelled data. 1 INTRODUCTION. During recent years, a new set of kernel ...
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Data domain description concerns the characterization of a data set. A good description covers all target data but includes no superfluous space.
Active learning based support vector data description method for robust novelty detection · Lili YinHuangang WangWenhui Fan. Computer Science, Engineering.
Another approach, the support vector data description. (SVDD) method, proposed by Tax and Duin [267], defines the novelty boundary as being the hypersphere with.