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Results tagged with regularization
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user 128939
Inclusion of additional constraints (typically a penalty for complexity) in the model fitting process. Used to prevent overfitting / enhance predictive accuracy.
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Regularization in Linear Regression
Regularization tends to decrease the variance of the estimators in exchange for some increase in bias. … If your model is well specified and there is only one predictor - there is no multicoliniarity by definition, and so if you've a reason to believe that the regression assumptions hold then adding a regularization …
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5
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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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Alternatives to glmnet for feature selection on data with lots of NAs
I'm working on something very similar as you. This is what I did:
In my feature space I had two kinds of variables - count variables and measure variables. Example for count: "Number of times test x w …
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6
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How can I calculate the number of degrees of freedom in the Elastic Net regularization, spec...
In the elastic net, and specifically in glment package in R - how would I obtain the number of degrees of freedom? Note that in the Glmnet Vignette it says that the df you get from the ouput after an …
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