Results 151 to 160 of about 1,354,633 (198)
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22nd Mediterranean Conference on Control and Automation, 2014
Abstract— The paper considers variable selection problem and proposes an algorithm called the RIVAL (Removing Irrelevant Variables Amidst Lasso Iterations). For a given and fixed length of data points, the algorithm recursively updates the weights so that the ability of the algorithm in detecting zero coefficients is substantially improved. Theoretical
Er-Wei Bai, Kang Li 0002, Paul Kump
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Abstract— The paper considers variable selection problem and proposes an algorithm called the RIVAL (Removing Irrelevant Variables Amidst Lasso Iterations). For a given and fixed length of data points, the algorithm recursively updates the weights so that the ability of the algorithm in detecting zero coefficients is substantially improved. Theoretical
Er-Wei Bai, Kang Li 0002, Paul Kump
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2020
In this chapter we survey Bayesian approaches for variable selection and model choice in regression models. We explore the methodological developments and computational approaches for these methods. In conclusion we note the available software for their implementation.
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In this chapter we survey Bayesian approaches for variable selection and model choice in regression models. We explore the methodological developments and computational approaches for these methods. In conclusion we note the available software for their implementation.
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A variable frequency, variable selectivity filter for electroencephalography
Electroencephalography and Clinical Neurophysiology, 1958Abstract An instrument is described which consists of simple revision of an inexpensive commercially available oscillator kit to allow its use both as an oscillator and a tunable frequency analyzer. These minor revisions, indicated in the electrical diagram, allow it to be coupled in the circuit of the EEG machine to accept single ended inputs of 1.5
H C, BECKER, W A, MICKLE, R G, HEATH
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Analysis of Clines with Variable Selection and Variable Migration
The American Naturalist, 2000We report a likelihood-based method that estimates both dispersal and natural selection using the rate of change of the shape of a cline when selection and migration are not constant through time. We have investigated the case of local adaptation of the mosquito Culex pipiens to organophosphate insecticides in the Montpellier area in France.
Thomas, Lenormand, Michel, Raymond
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Benefitting from the variables that variable selection discards
J. Mach. Learn. Res., 2003Summary: In supervised learning variable selection is used to find a subset of the available inputs that accurately predict the output. This paper shows that some of the variables that variable selection discards can beneficially be used as extra outputs for inductive transfer.
Rich Caruana, Virginia R. de Sa
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Selection of Variables in Mixed-Variable Discriminant Analysis
Biometrics, 1986A MANOVA-log-linear formulation of the location model for mix ed-variable discriminant analysis is considered. A strategy for the selection of variables and terms in such a model is based on Akaike's criterion. To overcome problems caused by noncomparable submodels, some modifications to Akaike's criterion are proposed.
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ON VARIABLE SELECTION IN LINEAR REGRESSION
Econometric Theory, 2002Shibata (1981, Biometrika 68, 45–54) considers data-generating mechanisms belonging to a certain class of linear regressions with errors that are independent and identically normally distributed. He compares the variable selection criteria AIC (Akaike information criterion) and BIC (Bayesian information criterion) using the following type of ...
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