Exact(3)
Unlike RR, some coefficients may shrink to zero, making LASSO especially useful for variable selection problems.
Like LASSO, it is particularly useful for variable selection in high-dimensional settings, producing sparse models that preserve predictive power and encourage grouping of correlated predictors.
Regularization techniques are particularly useful for variable selection in high-dimensional setting where the number of variables is much greater than the sample size and have gained increasing popularity.
Similar(57)
This study provided a novel examination of GA as a useful tool for variable selection in the context of questionnaire data.
Is the statistical method used for variable selection described?
The Wald statistic was used for variable selection.
A backward conditional selection method was used for variable selection by the model.
Backward selection with a cut-off P-value of 0.10 was used for variable selection.
Statistical factors were used for variable selections.
We used a genetic algorithm for variable selection.
We used stepwise regression [15] for variable selection.
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