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JMLR
2010
118views more  JMLR 2010»
13 years 3 days ago
Dirichlet Process Mixtures of Generalized Linear Models
We propose Dirichlet Process mixtures of Generalized Linear Models (DP-GLMs), a new method of nonparametric regression that accommodates continuous and categorical inputs, models ...
Lauren Hannah, David M. Blei, Warren B. Powell
COMPSAC
2001
IEEE
13 years 9 months ago
Scenario-Based Functional Regression Testing
Regression testing has been a popular quality assurance technique. Most regression testing techniques are based on code or software design. This paper proposes a scenario-based fu...
Raymond A. Paul, Lian Yu, Wei-Tek Tsai, Xiaoying B...
GECCO
2008
Springer
174views Optimization» more  GECCO 2008»
13 years 6 months ago
Mask functions for the symbolic modeling of epistasis using genetic programming
The study of common, complex multifactorial diseases in genetic epidemiology is complicated by nonlinearity in the genotype-to-phenotype mapping relationship that is due, in part,...
Ryan J. Urbanowicz, Nate Barney, Bill C. White, Ja...
CSDA
2006
145views more  CSDA 2006»
13 years 5 months ago
Improved predictions penalizing both slope and curvature in additive models
A new method is proposed to estimate the nonlinear functions in an additive regression model. Usually, these functions are estimated by penalized least squares, penalizing the cur...
Magne Aldrin
ESANN
2006
13 years 6 months ago
Using Regression Error Characteristic Curves for Model Selection in Ensembles of Neural Networks
Regression Error Characteristic (REC) analysis is a technique for evaluation and comparison of regression models that facilitates the visualization of the performance of many regre...
Aloísio Carlos de Pina, Gerson Zaverucha