Nothing
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
.Any scripts or data that you put into this service are public.
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