This paper introduces an alternative variable selection method for use in regression analysis that is based on the Tabu search procedure. The Tabu search was compared to traditional regression analysis procedures using various size data sets. The results indicate the superiority of the Tabu search procedure for model selection in multiple regression analysis
The main problem in regression model selection is finding the best model that best fits the data, i....
1 page, 1 article*Selection Criteria in Multiple Regression* (Cady, Foster B.) 1 pag
We give an example of the use of the forward search in building a regression model. The standard bac...
Abstract. We illustrate how a comparatively new technique, a Tabu search variable selection model [D...
The problem of determining the best subset has two important aspects: the choice of a criteria defin...
With advanced capability in data collection, applications of linear regression analysis now often in...
Simulation was used to evaluate the performances of several methods of variable selection in regress...
With the increasing use of models to evaluate agricultural systems and identify the best solutions, ...
This work illustrated the procedures in getting the best model using Multiple Regression. The Multip...
Analysis of data sets that involve large numbers of variables usually entails some type of model fit...
The main problem in regression model selection independently from application domain is finding the ...
The selection of a descriptor, X, is crucial for improving the interpretation and prediction accurac...
International audienceIn this paper, we investigate on 39 Variable Selection procedures to give an o...
Abstract In the design of classification models, irrelevant or noisy features are often generated. I...
This paper introduces a SAS/IML program to select among the multivariate model candidates based on a...
The main problem in regression model selection is finding the best model that best fits the data, i....
1 page, 1 article*Selection Criteria in Multiple Regression* (Cady, Foster B.) 1 pag
We give an example of the use of the forward search in building a regression model. The standard bac...
Abstract. We illustrate how a comparatively new technique, a Tabu search variable selection model [D...
The problem of determining the best subset has two important aspects: the choice of a criteria defin...
With advanced capability in data collection, applications of linear regression analysis now often in...
Simulation was used to evaluate the performances of several methods of variable selection in regress...
With the increasing use of models to evaluate agricultural systems and identify the best solutions, ...
This work illustrated the procedures in getting the best model using Multiple Regression. The Multip...
Analysis of data sets that involve large numbers of variables usually entails some type of model fit...
The main problem in regression model selection independently from application domain is finding the ...
The selection of a descriptor, X, is crucial for improving the interpretation and prediction accurac...
International audienceIn this paper, we investigate on 39 Variable Selection procedures to give an o...
Abstract In the design of classification models, irrelevant or noisy features are often generated. I...
This paper introduces a SAS/IML program to select among the multivariate model candidates based on a...
The main problem in regression model selection is finding the best model that best fits the data, i....
1 page, 1 article*Selection Criteria in Multiple Regression* (Cady, Foster B.) 1 pag
We give an example of the use of the forward search in building a regression model. The standard bac...