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
Learning from imperfect data
β Scribed by Pitoyo Hartono; Shuji Hashimoto
- Publisher
- Elsevier Science
- Year
- 2007
- Tongue
- English
- Weight
- 583 KB
- Volume
- 7
- Category
- Article
- ISSN
- 1568-4946
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