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» Learning Rule Representations from Boolean Data
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114
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EDM
2010
145views Data Mining» more  EDM 2010»
15 years 1 months ago
Mining Rare Association Rules from e-Learning Data
Rare association rules are those that only appear infrequently even though they are highly associated with very specific data. In consequence, these rules can be very appropriate f...
Cristóbal Romero, José Raúl R...
106
Voted
APIN
2004
81views more  APIN 2004»
15 years 9 days ago
Learning Generalized Policies from Planning Examples Using Concept Languages
In this paper we are concerned with the problem of learning how to solve planning problems in one domain given a number of solved instances. This problem is formulated as the probl...
Mario Martin, Hector Geffner
69
Voted
AAAI
1998
15 years 1 months ago
Feature Generation for Sequence Categorization
The problem of sequence categorization is to generalize from a corpus of labeled sequences procedures for accurately labeling future unlabeled sequences. The choice of representat...
Daniel Kudenko, Haym Hirsh
102
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KDD
1999
ACM
104views Data Mining» more  KDD 1999»
15 years 4 months ago
Learning Rules from Distributed Data
In this paper a concern about the accuracy (as a function of parallelism) of a certain class of distributed learning algorithms is raised, and one proposed improvement is illustrat...
Lawrence O. Hall, Nitesh V. Chawla, Kevin W. Bowye...
109
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DSS
2007
127views more  DSS 2007»
15 years 12 days ago
Large-scale regulatory network analysis from microarray data: modified Bayesian network learning and association rule mining
We present two algorithms for learning large-scale gene regulatory networks from microarray data: a modified informationtheory-based Bayesian network algorithm and a modified asso...
Zan Huang, Jiexun Li, Hua Su, George S. Watts, Hsi...