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» On learning algorithm selection for classification
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139
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ICDM
2009
IEEE
207views Data Mining» more  ICDM 2009»
14 years 12 months ago
Spatially Adaptive Classification and Active Learning of Multispectral Data with Gaussian Processes
Multispectral remote sensing images are widely used for automated land use and land cover classification tasks. Remotely sensed images usually cover large geographical areas, and s...
Goo Jun, Ranga Raju Vatsavai, Joydeep Ghosh
JMLR
2010
104views more  JMLR 2010»
14 years 9 months ago
Increasing Feature Selection Accuracy for L1 Regularized Linear Models
L1 (also referred to as the 1-norm or Lasso) penalty based formulations have been shown to be effective in problem domains when noisy features are present. However, the L1 penalty...
Abhishek Jaiantilal, Gregory Z. Grudic
115
Voted
CIKM
2006
Springer
15 years 6 months ago
Performance thresholding in practical text classification
In practical classification, there is often a mix of learnable and unlearnable classes and only a classifier above a minimum performance threshold can be deployed. This problem is...
Hinrich Schütze, Emre Velipasaoglu, Jan O. Pe...
3DOR
2010
14 years 9 months ago
Semantics-Driven Approach for Automatic Selection of Best Views of 3D Shapes
We introduce a new framework for the automatic selection of the best views of 3D models. The approach is based on the assumption that models belonging to the same class of shapes ...
Hamid Laga
143
Voted
CVPR
2009
IEEE
16 years 9 months ago
Shape Classification Through Structured Learning of Matching Measures
Many traditional methods for shape classification involve establishing point correspondences between shapes to produce matching scores, which are in turn used as similarity meas...
Longbin Chen, Julian John McAuley, Rogério ...