94 search results - page 12 / 19 » Inductive rule learning on the knowledge level |
SAC
2009
ACM
14 years 2 months ago
2009
ACM
Decision trees are widely disseminated as an effective solution for classification tasks. Decision tree induction algorithms have some limitations though, due to the typical strat...
DAGSTUHL
2004
13 years 9 months ago
2004
Subgroup discovery aims at finding interesting subsets of a classified example set that deviates from the overall distribution. The search is guided by a so-called utility function...
NIPS
2007
13 years 9 months ago
2007
Semi-supervised inductive learning concerns how to learn a decision rule from a data set containing both labeled and unlabeled data. Several boosting algorithms have been extended...
DATAMINE
2002
13 years 7 months ago
2002
Discrete values have important roles in data mining and knowledge discovery. They are about intervals of numbers which are more concise to represent and specify, easier to use and ...
JASIS
2000
13 years 7 months ago
2000
s In data mining, we emphasize the need for learning from huge, incomplete and imperfect data sets (Fayyad et al. 1996, Frawley et al. 1991, Piatetsky-Shapiro and Frawley, 1991). T...