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DIS
2006
Springer
13 years 11 months ago
Optimal Bayesian 2D-Discretization for Variable Ranking in Regression
In supervised machine learning, variable ranking aims at sorting the input variables according to their relevance w.r.t. an output variable. In this paper, we propose a new relevan...
Marc Boullé, Carine Hue
AUSAI
2008
Springer
13 years 9 months ago
Additive Regression Applied to a Large-Scale Collaborative Filtering Problem
Abstract. The much-publicized Netflix competition has put the spotlight on the application domain of collaborative filtering and has sparked interest in machine learning algorithms...
Eibe Frank, Mark Hall
NCI
2004
141views Neural Networks» more  NCI 2004»
13 years 9 months ago
Estimating the error at given test input points for linear regression
In model selection procedures in supervised learning, a model is usually chosen so that the expected test error over all possible test input points is minimized. On the other hand...
Masashi Sugiyama
ESANN
2000
13 years 9 months ago
Distributed clustering and local regression for knowledge discovery in multiple spatial databases
Many large -scale spatial data analysis problems involve an investigation of relationships in heterogeneous databases. In such situations, instead of making predictions uniformly a...
Aleksandar Lazarevic, Dragoljub Pokrajac, Zoran Ob...
GLOBECOM
2008
IEEE
14 years 2 months ago
Distributed Regression in Sensor Networks with a Reduced-Order Kernel Model
Abstract—Over the past few years, wireless sensor networks received tremendous attention for monitoring physical phenomena, such as the temperature field in a given region. Appl...
Paul Honeine, Mehdi Essoloh, Cédric Richard...