An Incremental Kernel Density Estimator for Data Stream Computation
Probability density function (p.d.f.) estimation plays a very important role in the field of data mining. Kernel density estimator (KDE) is the mostly used technology to estimate the unknown p.d.f. for the given dataset. The existing KDEs are usually inefficient when handling the p.d.f. estimation p...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/1803525 |
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