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» Interaction models for functional regression
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ICML
2008
IEEE
14 years 5 months ago
Detecting statistical interactions with additive groves of trees
Discovering additive structure is an important step towards understanding a complex multi-dimensional function because it allows the function to be expressed as the sum of lower-d...
Daria Sorokina, Rich Caruana, Mirek Riedewald, Dan...
NPL
2002
168views more  NPL 2002»
13 years 4 months ago
Reduced Rank Kernel Ridge Regression
Ridge regression is a classical statistical technique that attempts to address the bias-variance trade-off in the design of linear regression models. A reformulation of ridge regr...
Gavin C. Cawley, Nicola L. C. Talbot
AAAI
2011
12 years 4 months ago
Incorporating Boosted Regression Trees into Ecological Latent Variable Models
Important ecological phenomena are often observed indirectly. Consequently, probabilistic latent variable models provide an important tool, because they can include explicit model...
Rebecca A. Hutchinson, Li-Ping Liu, Thomas G. Diet...
BMCBI
2010
172views more  BMCBI 2010»
13 years 4 months ago
Inferring gene regression networks with model trees
Background: Novel strategies are required in order to handle the huge amount of data produced by microarray technologies. To infer gene regulatory networks, the first step is to f...
Isabel A. Nepomuceno-Chamorro, Jesús S. Agu...
BRAIN
2010
Springer
13 years 3 months ago
Sparse Regression Models of Pain Perception
Discovering brain mechanisms underlying pain perception remains a challenging neuroscientific problem with important practical applications, such as developing better treatments f...
Irina Rish, Guillermo A. Cecchi, Marwan N. Baliki,...