Resource-light method and apparatus for outlier detection
US8006157B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 28, 2007 |
| Grant date | Aug 23, 2011 |
| Priority date | — |
| Expiry date | Jun 22, 2030 |
Classification
- Technology area (CPC Y)Emerging Cross-Sectional Technologies
- CPC primaryY10S707/99943
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Outlier detection methods and apparatus have light computational resources requirement, especially on the storage requirement, and yet achieve a state-of-the-art predictive performance. The outlier detection problem is first reduced to that of a classification learning problem, and then selective sampling based on uncertainty of prediction is applied to further reduce the amount of data required for data analysis, resulting in enhanced predictive performance. The reduction to classification essentially consists in using the unlabeled normal data as positive examples, and randomly generated synthesized examples as negative examples. Application of selective sampling makes use of an underlying, arbitrary classification learning algorithm, the data labeled by the above procedure, and proceeds iteratively. Each iteration consisting of selection of a smaller sub-sample from the input data, training of the underlying classification algorithm with the selected data, and storing the classifier output by the classification algorithm. The selection is done by essentially choosing examples that are harder to classify with the classifiers obtained in the preceding iterations. The final output …
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.