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JMLR
2002
106views more  JMLR 2002»
14 years 9 months ago
Some Greedy Learning Algorithms for Sparse Regression and Classification with Mercer Kernels
We present some greedy learning algorithms for building sparse nonlinear regression and classification models from observational data using Mercer kernels. Our objective is to dev...
Prasanth B. Nair, Arindam Choudhury 0002, Andy J. ...
AICCSA
2006
IEEE
121views Hardware» more  AICCSA 2006»
14 years 11 months ago
Software Defect Prediction Using Regression via Classification
In this paper we apply a machine learning approach to the problem of estimating the number of defects called Regression via Classification (RvC). RvC initially automatically discr...
Stamatia Bibi, Grigorios Tsoumakas, Ioannis Stamel...
ICML
2005
IEEE
15 years 10 months ago
Incomplete-data classification using logistic regression
A logistic regression classification algorithm is developed for problems in which the feature vectors may be missing data (features). Single or multiple imputation for the missing...
David Williams, Xuejun Liao, Ya Xue, Lawrence Cari...
PAMI
2006
208views more  PAMI 2006»
14 years 9 months ago
Combining Reconstructive and Discriminative Subspace Methods for Robust Classification and Regression by Subsampling
Linear subspace methods that provide sufficient reconstruction of the data, such as PCA, offer an efficient way of dealing with missing pixels, outliers, and occlusions that often ...
Sanja Fidler, Danijel Skocaj, Ales Leonardis
SDM
2004
SIAM
242views Data Mining» more  SDM 2004»
14 years 11 months ago
Privacy-Preserving Multivariate Statistical Analysis: Linear Regression and Classification
Multivariate statistical analysis is an important data analysis technique that has found applications in various areas. In this paper, we study some multivariate statistical analy...
Wenliang Du, Yunghsiang S. Han, Shigang Chen