Hidden features extraction using Independent Component Analysis for improved alert clustering
Feature extraction plays an important role in reducing the computational complexity and increasing the accuracy. Independent Component Analysis (ICA) is an effective feature extraction technique for disclosing hidden factors that underlying mixed samples of random variable measurements. The computat...
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| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Published: |
2015
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/59297/ http://dx.doi.org/10.1109/I4CT.2015.7219631 |
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