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» The Complexity of Forecast Testing
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145
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AUSDM
2008
Springer
211views Data Mining» more  AUSDM 2008»
15 years 6 months ago
LBR-Meta: An Efficient Algorithm for Lazy Bayesian Rules
LBR is a highly accurate classification algorithm, which lazily constructs a single Bayesian rule for each test instance at classification time. However, its computational complex...
Zhipeng Xie
144
Voted
ENTCS
2008
87views more  ENTCS 2008»
15 years 4 months ago
A Lightweight Approach for the Semantic Validation of Model Refinements
Model Driven Engineering proposes the use of models at different levels of ion. Step by step validation of model refinements is necessary to guarantee the correctness of the final ...
Claudia Pons, Diego García
JAIR
2008
120views more  JAIR 2008»
15 years 4 months ago
Anytime Induction of Low-cost, Low-error Classifiers: a Sampling-based Approach
Machine learning techniques are gaining prevalence in the production of a wide range of classifiers for complex real-world applications with nonuniform testing and misclassificati...
Saher Esmeir, Shaul Markovitch
KDD
2006
ACM
164views Data Mining» more  KDD 2006»
16 years 5 months ago
Assessing data mining results via swap randomization
The problem of assessing the significance of data mining results on high-dimensional 0?1 data sets has been studied extensively in the literature. For problems such as mining freq...
Aristides Gionis, Heikki Mannila, Panayiotis Tsapa...
BMCBI
2008
105views more  BMCBI 2008»
15 years 4 months ago
Using the longest significance run to estimate region-specific p-values in genetic association mapping studies
Background: Association testing is a powerful tool for identifying disease susceptibility genes underlying complex diseases. Technological advances have yielded a dramatic increas...
Ie-Bin Lian, Yi-Hsien Lin, Ying-Chao Lin, Hsin-Cho...