Abstract
We present a method for discovering informative patterns from data. With this method, large databases can be reduced to only a few representative data entries. Our framework also encompasses methods for cleaning databases containing corrupted data. Both on-line and off-line algorithms are proposed and experimentally checked on databases of handwritten images. The generality of the framework makes it an attractive candidate for new applications in knowledge discovery. Keywords: knowledge discovery, machine learning, informative patterns, data cleaning, information gain. 4.1
Keywords
GeneralityComputer scienceData miningData modelingLine (geometry)Information retrievalArtificial intelligenceDatabase
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Publication Info
- Year
- 1996
- Type
- article
- Pages
- 181-203
- Citations
- 234
- Access
- Closed
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Cite This
Isabelle Guyon,
Nada Matic,
Vladimir Vapnik
(1996).
Discovering informative patterns and data cleaning.
, 181-203.