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ICDM
2007
IEEE
150views Data Mining» more  ICDM 2007»
15 years 10 months ago
Connections between Mining Frequent Itemsets and Learning Generative Models
Frequent itemsets mining is a popular framework for pattern discovery. In this framework, given a database of customer transactions, the task is to unearth all patterns in the for...
Srivatsan Laxman, Prasad Naldurg, Raja Sripada, Ra...
NN
2006
Springer
114views Neural Networks» more  NN 2006»
15 years 4 months ago
Modular learning models in forecasting natural phenomena
Modular model is a particular type of committee machine and is comprised of a set of specialized (local) models each of which is responsible for a particular region of the input s...
Dimitri P. Solomatine, Michael Baskara L. A. Siek
FMOODS
2006
15 years 5 months ago
Generating Instance Models from Meta Models
Meta modeling is a wide-spread technique to define visual languages, with the UML being the most prominent one. Despite several advantages of meta modeling such as ease of use, the...
Karsten Ehrig, Jochen Malte Küster, Gabriele ...
BMCBI
2005
126views more  BMCBI 2005»
15 years 4 months ago
GANN: Genetic algorithm neural networks for the detection of conserved combinations of features in DNA
Background: The multitude of motif detection algorithms developed to date have largely focused on the detection of patterns in primary sequence. Since sequence-dependent DNA struc...
Robert G. Beiko, Robert L. Charlebois
EDM
2010
248views Data Mining» more  EDM 2010»
15 years 6 months ago
Analyzing Learning Styles using Behavioral Indicators in Web based Learning Environments
It is argued that the analysis of the learner's generated log files during interactions with a learning environment is necessary to produce interpretative views of their activ...
Nabila Bousbia, Jean-Marc Labat, Amar Balla, Issam...