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» A New Class Based Associative Classification Algorithm
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192
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BMCBI
2006
198views more  BMCBI 2006»
15 years 2 months ago
Gene selection and classification of microarray data using random forest
Background: Selection of relevant genes for sample classification is a common task in most gene expression studies, where researchers try to identify the smallest possible set of ...
Ramón Díaz-Uriarte, Sara Alvarez de ...
104
Voted
LREC
2010
206views Education» more  LREC 2010»
15 years 3 months ago
Efficient Multilabel Classification Algorithms for Large-Scale Problems in the Legal Domain
In this paper we evaluate the performance of multilabel classification algorithms on the EUR-Lex database of legal documents of the European Union. On the same set of underlying d...
Eneldo Loza Mencía, Johannes Fürnkranz
JCST
2008
119views more  JCST 2008»
15 years 2 months ago
Mining Frequent Generalized Itemsets and Generalized Association Rules Without Redundancy
This paper presents some new algorithms to efficiently mine max frequent generalized itemsets (g-itemsets) and essential generalized association rules (g-rules). These are compact ...
Daniel Kunkle, Donghui Zhang, Gene Cooperman
VLDB
1998
ACM
127views Database» more  VLDB 1998»
15 years 6 months ago
Algorithms for Mining Association Rules for Binary Segmentations of Huge Categorical Databases
We consider the problem of finding association rules that make nearly optimal binary segmentations of huge categorical databases. The optimality of segmentation is defined by an o...
Yasuhiko Morimoto, Takeshi Fukuda, Hirofumi Matsuz...
122
Voted
ICCV
2005
IEEE
16 years 4 months ago
A New Framework for Approximate Labeling via Graph Cuts
A new framework is presented that uses tools from duality theory of linear programming to derive graph-cut based combinatorial algorithms for approximating NP-hard classification ...
Nikos Komodakis, Georgios Tziritas