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» Bayesian Algorithms for Causal Data Mining
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KDD
1995
ACM
109views Data Mining» more  KDD 1995»
13 years 11 months ago
An Iterative Improvement Approach for the Discretization of Numeric Attributes in Bayesian Classifiers
The Bayesianclassifier is a simple approachto classification that producesresults that are easy for people to interpret. In many cases, the Bayesianclassifieris at leastasaccurate...
Michael J. Pazzani
ASC
2011
13 years 2 months ago
A rough set approach to multiple dataset analysis
In the area of data mining, the discovery of valuable changes and connections (e.g., causality) from multiple data sets has been recognized as an important issue. This issue essen...
Ken Kaneiwa
ICDM
2007
IEEE
184views Data Mining» more  ICDM 2007»
14 years 1 months ago
Bayesian Folding-In with Dirichlet Kernels for PLSI
Probabilistic latent semantic indexing (PLSI) represents documents of a collection as mixture proportions of latent topics, which are learned from the collection by an expectation...
Alexander Hinneburg, Hans-Henning Gabriel, Andr&eg...
EDM
2008
169views Data Mining» more  EDM 2008»
13 years 8 months ago
Mining Student Behavior Models in Learning-by-Teaching Environments
This paper discusses our approach to building models and analyzing student behaviors in different versions of our learning by teaching environment where students learn by teaching ...
Hogyeong Jeong, Gautam Biswas
SDM
2010
SIAM
149views Data Mining» more  SDM 2010»
13 years 8 months ago
Temporal Collaborative Filtering with Bayesian Probabilistic Tensor Factorization
Real-world relational data are seldom stationary, yet traditional collaborative filtering algorithms generally rely on this assumption. Motivated by our sales prediction problem, ...
Liang Xiong, Xi Chen, Tzu-Kuo Huang, Jeff Schneide...