Abstract
To provide good feature selection for sequential domains, FeatureMine was developed. This scalable feature-mining algorithm combines sequence mining and classification algorithms. Tests on three practical domains demonstrate the capability to efficiently handle very large data sets with thousands of items and millions of records.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 48-56 |
| Number of pages | 9 |
| Journal | IEEE Intelligent Systems and Their Applications |
| Volume | 15 |
| Issue number | 2 |
| State | Published - Jan 1 2000 |
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ASJC Scopus subject areas
- Engineering(all)
Cite this
Lesh, N., Zaki, M. J., & Ogihara, M. (2000). Scalable feature mining for sequential data. IEEE Intelligent Systems and Their Applications, 15(2), 48-56.