plot.cva.glmnet:
log.x controls whether to plot the X-axis (lambda) on the
log scale, and the legend can be omitted by setting either
legend.x or legend.y to
NULL.glmnet.formula object.glmnet.formula and cv.glmnet.formula (requires
glmnet 3.0 or later).cva.glmnet object.cva.glmnet. The impact is most serious for small
datasets, where the number of observations per fold is relatively low.
If you are using this function, it’s highly recommended you update the
package.nfolds argument was not being passed to
glmnet::cv.glmnet.use.model.frame=TRUE. This works in an additive fashion, ie
the formula ~ a + b:c + d*e is treated as consisting of
three terms, a, b:c and d*e each
of which is processed independently of the others. A dot in the formula
includes all main effect terms, ie ~ . + a:b + f(x) expands
to ~ a + b + x + a:b + f(x) (assuming a, b and x are the
only columns in the data). Note that a formula like
~ (a + b) + (c + d) will be treated as two terms,
a + b and c + d.glmnet/cv.glmnet
object that uses the original matrix/vector interface is now
useful.cva.glmnet.
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