Meena, Lakhpat and Devi, Susheela V (2015) Prototype Selection on Large and Streaming Data. In: 22nd International Conference on Neural Information Processing (ICONIP), NOV 09-12, 2015, Istanbul, TURKEY, pp. 671-679.
Full text not available from this repository. (Request a copy)Abstract
Since streaming data keeps coming continuously as an ordered sequence, massive amounts of data is created. A big challenge in handling data streams is the limitation of time and space. Prototype selection on streaming data requires the prototypes to be updated in an incremental manner as new data comes in. We propose an incremental algorithm for prototype selection. This algorithm can also be used to handle very large datasets. Results have been presented on a number of large datasets and our method is compared to an existing algorithm for streaming data. Our algorithm saves time and the prototypes selected gives good classification accuracy.
| Item Type: | Conference Proceedings |
|---|---|
| Series.: | Lecture Notes in Computer Science |
| Publisher: | SPRINGER INT PUBLISHING AG |
| Additional Information: | Copy right for this article belongs to the SPRINGER INT PUBLISHING AG, GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND |
| Keywords: | Prototype selection; One-pass algorithm; Streaming data |
| Department/Centre: | Division of Biological Sciences > Microbiology & Cell Biology |
| Date Deposited: | 28 Apr 2016 05:03 |
| Last Modified: | 28 Apr 2016 05:03 |
| URI: | http://eprints.iisc.ac.in/id/eprint/53639 |
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