Examples of 'variable selection' in a sentence

Meaning of "variable selection"

Variable selection refers to the process of choosing which variables or predictors to include in a statistical model. It is important in order to model and analyze data accurately and effectively. This process involves identifying the most relevant and significant variables while removing any redundant or irrelevant ones

How to use "variable selection" in a sentence

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variable selection
Moreover variable selection consistency is also established.
The method used was forward variable selection.
A stepwise variable selection process was employed.
We adopted the backward procedure of variable selection.
Variable selection for regression estimation in finite populations.
Stepwise approach for variable selection was used.
For variable selection was used the stepwise backward method.
Description of the variable selection mode.
The variable selection study by means of procrusts analysis was also carried out.
A forward likelihood ratio approach was applied for variable selection.
The backward method for variable selection was used as no explanatory model was available.
In this thesis we study several aspects of the variable selection problem.
Advances in variable selection and visualization methods for analysis of multivariate data.
The model fitting can include both variable selection and parameter estimation.
Variable selection terminates when no more variables meet entry and removal criteria.

See also

This thesis proposes methods for variable selection aimed at classifying production batches.
Variable selection is a collection of candidate model variables tested for significance during model training.
The third chapter deals with variable selection problem using sparse approaches.
Numerical examples demonstrate the usefulness of these methods in terms of variable selection and clustering.
The stepwise variable selection method with backward elimination was used in the adjusted analysis.
Comparison of Bayesian predictive methods for variable selection.
Different strategies of forecast combinations and variable selection procedures for multivariate methods were contemplated.
Variable selection The variables selected for matching must fulfil two criteria.
This thesis test an approach to variable selection aimed at clustering and classifying drug samples.
The backward method Wald was used for variable selection.
This thesis proposes new approaches for variable selection aimed at forming representative groups of observations.
Variable selection for high-dimensional data.
Typical preventive measures during variable selection include,.
The stepwise variable selection method was used and the significance level was 5 % p.
After univariate analysis, there was a multivariate stepwise criterion variable selection.
When you do this, a variable selection box will appear.
Of course, the invention is not limited to these particular elementary variable selection criteria.
In a second part, we introduce a variable selection methodology for smooth transition.
Two variable selection methods ( a filter and a wrapper method ) that exploit problem-specific characteristics are proposed.
Firstly, we consider the problem of group variable selection in multi-class logistic regression.
We propose a variable selection procedure for clustering suited to high-dimensional contexts.
Moreover, we recover optimal necessary and sufficient conditions for variable selection in this model.
As a result, a variable selection of organic compounds of selenium can be formed in the yeast.
For the adjusted analysis, we used the method of stepwise variable selection with backward elimination.
Abstract, We are interested in variable selection for clustering with Gaussian mixture models.
Again, an FVS algorithm can be used as a variable selection technique.
Chapter 4 is dedicated to variable selection in general mixed-e ffects models.
Abstract, This thesis is concerned with variable selection in two practical problems.
In Chapter 4, we propose a penalized criterion for variable selection in supervised classi ¯ cation.

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