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PKDD
2010
Springer
169views Data Mining» more  PKDD 2010»
13 years 5 months ago
Efficient and Numerically Stable Sparse Learning
We consider the problem of numerical stability and model density growth when training a sparse linear model from massive data. We focus on scalable algorithms that optimize certain...
Sihong Xie, Wei Fan, Olivier Verscheure, Jiangtao ...
BMCBI
2008
219views more  BMCBI 2008»
13 years 8 months ago
Classification of premalignant pancreatic cancer mass-spectrometry data using decision tree ensembles
Background: Pancreatic cancer is the fourth leading cause of cancer death in the United States. Consequently, identification of clinically relevant biomarkers for the early detect...
Guangtao Ge, G. William Wong
CORR
2010
Springer
74views Education» more  CORR 2010»
13 years 8 months ago
Significance of Classification Techniques in Prediction of Learning Disabilities
The aim of this study is to show the importance of two classification techniques, viz. decision tree and clustering, in prediction of learning disabilities (LD) of school-age chil...
Julie M. David, Kannan Balakrishnan
SGAI
2009
Springer
14 years 2 months ago
Parallel Rule Induction with Information Theoretic Pre-Pruning
In a world where data is captured on a large scale the major challenge for data mining algorithms is to be able to scale up to large datasets. There are two main approaches to indu...
Frederic T. Stahl, Max Bramer, Mo Adda
EGH
2011
Springer
12 years 7 months ago
Simpler and Faster HLBVH with Work Queues
A recently developed algorithm called Hierachical Linear Bounding Volume Hierarchies (HLBVH) has demonstrated the feasibility of reconstructing the spatial index needed for ray tr...
Kirill Garanzha, Jacopo Pantaleoni, David K. McAll...