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» The Problems of Data Modeling in Software Practice
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DATAMINE
2010
133views more  DATAMINE 2010»
15 years 4 months ago
Using background knowledge to rank itemsets
Assessing the quality of discovered results is an important open problem in data mining. Such assessment is particularly vital when mining itemsets, since commonly many of the disc...
Nikolaj Tatti, Michael Mampaey
155
Voted
JCST
2010
139views more  JCST 2010»
15 years 2 months ago
Dirichlet Process Gaussian Mixture Models: Choice of the Base Distribution
In the Bayesian mixture modeling framework it is possible to infer the necessary number of components to model the data and therefore it is unnecessary to explicitly restrict the n...
Dilan Görür, Carl Edward Rasmussen
140
Voted
CORR
2010
Springer
207views Education» more  CORR 2010»
15 years 4 months ago
Collaborative Hierarchical Sparse Modeling
Sparse modeling is a powerful framework for data analysis and processing. Traditionally, encoding in this framework is performed by solving an 1-regularized linear regression prob...
Pablo Sprechmann, Ignacio Ramírez, Guillerm...
146
Voted
DEXA
2008
Springer
176views Database» more  DEXA 2008»
15 years 5 months ago
Inventing Less, Reusing More, and Adding Intelligence to Business Process Modeling
Recently, a variety of workflow patterns has been proposed focusing on specific aspects like control flow, data flow, and resource assignments. Though these patterns are relevant f...
Lucinéia Heloisa Thom, Manfred Reichert, Ca...
ARTMED
1999
92views more  ARTMED 1999»
15 years 3 months ago
Two-Stage Machine Learning model for guideline development
We present a Two-Stage Machine Learning (ML) model as a data mining method to develop practice guidelines and apply it to the problem of dementia staging. Dementia staging in clin...
Subramani Mani, William Rodman Shankle, Malcolm B....