Comments (5)
I think that the way of calculation by caret is inefficient when you use it for the grid search on alpha and lambda at the same time for glmnet. The point is that the glmnet function is slow when you supply a single value for lambda (but the grid search does repeat "supplying a single value for lambda").
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Thank you for your advice, Iwasawa-san.
I understood your point. Maybe measuring time of glmnet for enough size of design matrices is the first task.
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By the way, you should anyway examine what glmnetUtils::cva.glmnet
can do.
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Implemented base function in #35 .
I will do more works for parallel computations, etc soon.
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Done in #61.
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Related Issues (20)
- Small changes HOT 1
- predict.aglm should accept a cv.aglm object HOT 3
- Doesn't "add_linear_columns = FALSE" work? HOT 1
- newoffset for predict.glmnet HOT 1
- Change names? HOT 2
- predict.AccurateGLM with type = "coefficients" or "nonzero" HOT 1
- Line 97 in 2904927 HOT 1
- Keep fit.preval, etc. in cv.aglm() HOT 1
- Set license HOT 2
- logical features
- Formula input HOT 1
- Partial residuals HOT 3
- Error with predict function HOT 2
- Defaults of type.measure HOT 1
- An additional option of plot.AccurateGLM HOT 4
- Another additional option of plot.AccurateGLM HOT 1
- L dummy option HOT 2
- install_github in case of not installing glmnet HOT 2
- Heavy vignettes
- Tests for more datasets
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