# Data Stream Mining Techniques

**Type:** Topics  
**Canonical URL:** https://scholariq.org/topics/data-stream-mining-techniques-2/

## Facts

| Field | Value |
| --- | --- |
| Citations | 274,006 |
| Description | This cluster of papers focuses on the adaptation to concept drift in data streams, particularly in the context of ensemble learning, adaptive algorithms, and online learning. It addresses challenges such as change detection, class imbalance, and incremental learning in streaming data environments. |
| Domain | Physical Sciences |
| Field | Computer Science |
| OpenAlex ID | https://openalex.org/T12761 |
| Works | 21,030 |

## Topic researchers

Showing 12 of 20.

- [Michael I. Jordan](https://scholariq.org/researchers/michael-i-jordan/)
- [David Silver](https://scholariq.org/researchers/david-silver/)
- [Koray Kavukcuoglu](https://scholariq.org/researchers/koray-kavukcuoglu/)
- [Anil K. Jain](https://scholariq.org/researchers/anil-k-jain/)
- [Bernhard Schölkopf](https://scholariq.org/researchers/bernhard-scholkopf/)
- [Francisco Herrera](https://scholariq.org/researchers/francisco-herrera/)
- [Richard Socher](https://scholariq.org/researchers/richard-socher/)
- [Philip S. Yu](https://scholariq.org/researchers/philip-s-yu/)
- [Serge Belongie](https://scholariq.org/researchers/serge-belongie/)
- [Andrew Y. Ng](https://scholariq.org/researchers/andrew-y-ng/)
- [Pietro Perona](https://scholariq.org/researchers/pietro-perona/)
- [Emmanuel J. Candès](https://scholariq.org/researchers/emmanuel-j-candes/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.