Concept drift detection for data stream learning based on angle optimized global embedding and principal component analysis in sensor networks
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: 2017DOI: 10.1016/j.compeleceng.2016.09.006
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Concept drift detection for data stream learning based on angle optimized global embedding and principal component analysis in sensor networks
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| contributor author | Shenglan Liu | |
| contributor author | Lin Feng | |
| contributor author | Jun Wu | |
| contributor author | Gang Hou | |
| contributor author | Guangjie Han | |
| date accessioned | 2020-03-15T08:51:40Z | |
| date available | 2020-03-15T08:51:40Z | |
| date issued | 2017 | |
| identifier other | EtOTQ3eYUqGbLCAI3veewchWvuRZUcjikGpCofPpx7H9Yooq7o.pdf | |
| identifier uri | https://libsearch.um.ac.ir:443/fum/handle/fum/1898594?locale-attribute=en | |
| format | general | |
| language | English | |
| title | Concept drift detection for data stream learning based on angle optimized global embedding and principal component analysis in sensor networks | |
| type | Journal Paper | |
| contenttype | Fulltext | |
| contenttype | Fulltext | |
| identifier padid | 13308466 | |
| identifier doi | 10.1016/j.compeleceng.2016.09.006 | |
| journal title | Computers & Electrical Engineering | |
| coverage | Academic | |
| filesize | 1072056 | |
| citations | 1 |