Online feature selection for mining big data
Most studies of online learning require accessing all the attributes/ features of training instances. Such a classical setting is not always appropriate for real-world applications when data instances are of high dimensionality or the access to it is expensive to acquire the full set of attributes/f...
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| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2013
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/98983 http://hdl.handle.net/10220/12629 |
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| Institution: | Nanyang Technological University |
| Language: | English |