Penalized regression with correlation-based penalty
نویسندگان
چکیده
منابع مشابه
Penalized regression with correlation-based penalty
A new regularization method for regression models is proposed. The criterion to be minimized contains a penalty term which explicitly links strength of penalization to the correlation between predictors. As the elastic net, the method encourages a grouping effect where strongly correlated predictors tend to be in or out of the model together. A boosted version of the penalized estimator, which ...
متن کاملwww.econstor.eu Penalized Regression with Correlation Based Penalty
A new regularization method for regression models is proposed. The criterion to be minimized contains a penalty term which explicitly links strength of penalization to the correlation between predictors. As the elastic net, the method encourages a grouping effect where strongly correlated predictors tend to be in or out of the model together. A boosted version of the penalized estimator, which ...
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Variable selection in linear regression can be challenging, particularly in situations where a large number of predictors is available with possibly high correlations , such as gene expression data. In this paper we propose a new method called the elastic corr-net to simultaneously select variables and encourage a grouping effect where strongly correlated predictors tend to be in or out of the ...
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Nonparametric regression techniques such as spline smoothing and local tting depend implicitly on a parametric model. For instance, the cubic smoothing spline estimate of a regression function based on observations ti; Yi is the minimizer of P(Yi (ti))2 + R ( 00)2. Since R ( 00)2 is zero when is a line, the cubic smoothing spline estimate favors the parametric model (t) = 0+ 1t: Here we conside...
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ژورنال
عنوان ژورنال: Statistics and Computing
سال: 2008
ISSN: 0960-3174,1573-1375
DOI: 10.1007/s11222-008-9088-5