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Results tagged with lasso
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user 128939
A regularization method for regression models that shrinks coefficients towards zero, making some of them equal to zero. Thus lasso performs feature selection.
5
votes
Accepted
L1-regularization enforces sparsity for convex functions
Regarding your question about general convex functions, you will get a sparse solution given that you apply a sparsity-inducing norm (which l1 is one such norm). For further information, read up to se …
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1
vote
1
answer
1k
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Why Ridge regularization has the grouping effect [duplicate]
I want to use elastic net (lasso + ridge) method for feature selection process. I can't understand why does the ridge method gives me the grouping effect for correlated variables. …
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3
votes
Report coefficients in elastic net regression after cross validation
Regarding your question about post-selection confidence intervals for the LASSO look for a paper by Tibshirani et al. titled "Exact Post-Selection Inference for Sequential Regression Procedures". …
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1
vote
1
answer
58
views
Preparation for modeling: how to deal with a huge number of variables
I read here that some people suggested LASSO or PCA. … It might be that x_1 alone gets dropped out by LASSO, but there is important information at the intersection between x_1 and x_2 that I miss. …
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