Current data-mining practice employs relatively low-level machine learning algorithms-statistical, neural-net, genetic, decision-tree, etc.-to trawl large data-sets for new classifiers. Usefulness of classifiers is then assessed according to accuracy in classifying new data, e.g. for stockmarket pre
โฆ LIBER โฆ
Learning temporal concepts from heterogeneous data sequences
โ Scribed by S. I. McClean; B. W. Scotney; F. L. Palmer
- Publisher
- Springer
- Year
- 2003
- Tongue
- English
- Weight
- 292 KB
- Volume
- 8
- Category
- Article
- ISSN
- 1432-7643
No coin nor oath required. For personal study only.
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