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SGAI
2009
Springer
13 years 11 months ago
Parallel Rule Induction with Information Theoretic Pre-Pruning
In a world where data is captured on a large scale the major challenge for data mining algorithms is to be able to scale up to large datasets. There are two main approaches to indu...
Frederic T. Stahl, Max Bramer, Mo Adda
SLOGICA
2008
120views more  SLOGICA 2008»
13 years 4 months ago
Emergence of Information Transfer by Inductive Learning
We study a simple game theoretic model of information transfer which we consider to be a baseline model for capturing strategic aspects of epistemological questions. In particular,...
Simon M. Huttegger, Brian Skyrms
KBS
2002
141views more  KBS 2002»
13 years 4 months ago
Using J-pruning to reduce overfitting in classification trees
The automatic induction of classification rules from examples in the form of a decision tree is an important technique used in data mining. One of the problems encountered is the o...
Max Bramer
IPM
2006
171views more  IPM 2006»
13 years 4 months ago
Automatic extraction of bilingual word pairs using inductive chain learning in various languages
In this paper, we propose a new learning method for extracting bilingual word pairs from parallel corpora in various languages. In cross-language information retrieval, the system...
Hiroshi Echizen-ya, Kenji Araki, Yoshio Momouchi
ENC
2004
IEEE
13 years 8 months ago
Efficient Data Structures and Parallel Algorithms for Association Rules Discovery
Discovering patterns or frequent episodes in transactions is an important problem in data-mining for the purpose of infering deductive rules from them. Because of the huge size of...
Christophe Cérin, Gay Gay, Gaël Le Mah...