LASSO-LARS CV System
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A LASSO-LARS CV System is a LASSO Cross-Validation System that implements a LARS Algorithm to solve a LASSO-LARS CV Task.
- AKA: LASSO-LARS Cross-Validation System.
- Example(s):
- Counter-Example(s):
- See: Cross-Validation Task, L1-Norm.
References
2017
- (Scikit Learn, 2017) ⇒ http://scikit-learn.org/stable/modules/linear_model.html#using-cross-validation Retrieved:2017-09-17
- QUOTE: scikit-learn exposes objects that set the Lasso
alpha
parameter by cross-validation:LassoCV
andLassoLarsCV
.LassoLarsCV
</a> is based on the Least Angle Regression algorithm explained below.For high-dimensional datasets with many collinear regressors,
LassoCV
is most often preferable. However,LassoLarsCV
has the advantage of exploring more relevant values of alpha parameter, and if the number of samples is very small compared to the number of features, it is often faster thanLassoCV
.
- QUOTE: scikit-learn exposes objects that set the Lasso