don't turn sparse matrix into dense matrix for glmnet prediction #1210
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EmilHvitfeldt
commented
Sep 30, 2024
| @@ -249,7 +249,7 @@ set_pred( | |||
| args = | |||
| list( | |||
| object = expr(object$fit), | |||
| newx = expr(as.matrix(new_data[, rownames(object$fit$beta), drop = FALSE])), | |||
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before we would call as.matrix() on anything before passing it to the predict method for the engine.
However if the data is a sparse matrix, we don't want to do that as {glmnet} is happy to receive it
simonpcouch
approved these changes
Oct 2, 2024
|
i got it done with some mocking 🎉 |
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What the title says:
there isn't really an easy way to test for this. This doesn't show up in our current tests as this is outside the scope of {sparsevctrs}