17 search results - page 1 / 4 » Optimal Bayesian 2D-Discretization for Variable Ranking in R... |
DIS
2006
Springer
13 years 8 months ago
2006
Springer
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...
ICCV
2009
IEEE
13 years 2 months ago
2009
IEEE
Poisson regression models the noisy output of a counting function as a Poisson random variable, with a log-mean parameter that is a linear function of the input vector. In this wo...
IJON
2007
13 years 4 months ago
2007
This paper addresses the problem of variable ranking for Support Vector Regression. The relevance criteria that we proposed are based on leave-one-out bounds and some variants and...
ICASSP
2011
IEEE
12 years 8 months ago
2011
IEEE
Reduced rank regression (RRR) has found application in various fields of signal processing. In this paper we propose a novel extension of the RRR model which we call sparse varia...
NPL
2002
13 years 4 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...