IPMI
2011
Springer
13 years 2 months ago
2011
Springer
Many current medical image analysis problems involve learning thousands or even millions of model parameters from extremely few samples. Employing sparse models provides an effecti...
INFORMATICALT
2011
13 years 6 months ago
2011
It is well known that in situations involving the study of large datasets where influential observations or outliers maybe present, regression models based on the Maximum Likeliho...
NPL
2002
13 years 11 months ago
2002
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...
CSDA
2010
13 years 11 months ago
2010
We consider switching regression models with independent or Markov-dependent regime. Based on the modified likelihood ratio test (LRT) statistic by Chen, Chen and Kalbfleisch (200...
CSDA
2010
13 years 11 months ago
2010
Linear regression models for de facto exchange rate regime classification are complemented by inferential techniques for evaluating the stability of the regimes. To simultaneously...
CGF
2010
13 years 11 months ago
2010
During the development of car engines, regression models that are based on machine learning techniques are increasingly important for tasks which require a prediction of results i...
SDM
2004
SIAM
14 years 26 days ago
2004
SIAM
This paper explores a novel framework for building regression models using association rules. The model consists of an ordered set of IF-THEN rules, where the rule consequent is t...
NIPS
2001
14 years 26 days ago
2001
We present an extension to the Mixture of Experts (ME) model, where the individual experts are Gaussian Process (GP) regression models. Using an input-dependent adaptation of the ...
ESANN
2006
14 years 27 days ago
2006
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...
ESEM
2008
ACM
14 years 1 months ago
2008
ACM
To construct a better multivariate regression model for software effort estimation, this paper proposes a method to select projects as a fit data from a given project data set bas...