corplot {pre} | R Documentation |
Plot correlations between baselearners in a prediction rule ensemble (pre)
Description
corplot
plots correlations between baselearners in a prediction rule ensemble
Usage
corplot(
object,
penalty.par.val = "lambda.1se",
colors = NULL,
fig.plot = c(0, 0.85, 0, 1),
fig.legend = c(0.8, 0.95, 0, 1),
legend.breaks = seq(-1, 1, by = 0.1)
)
Arguments
object |
object of class pre
|
penalty.par.val |
character or numeric. Value of the penalty parameter
\lambda to be employed for selecting the final ensemble. The default
"lambda.min" employs the \lambda value within 1 standard
error of the minimum cross-validated error. Alternatively,
"lambda.min" may be specified, to employ the \lambda value
with minimum cross-validated error, or a numeric value >0 may be
specified, with higher values yielding a sparser ensemble. To evaluate the
trade-off between accuracy and sparsity of the final ensemble, inspect
pre_object$glmnet.fit and plot(pre_object$glmnet.fit) .
|
colors |
vector of contiguous colors to be used for plotting. If
colors = NULL (default), colorRampPalette is used to generate
a sequence of 200 colors going from red to white to blue. A different set of
plotting colors can be specified here, for example:
cm.colors(100) , rainbow_hcl)(100) (the latter requires
package colorspace ).
or colorRampPalette(c("red", "yellow", "green"))(100) .
|
fig.plot |
plotting region to be used for correlation plot. See
fig under par .
|
fig.legend |
plotting region to be used for legend. See fig
under par .
|
legend.breaks |
numeric vector of breakpoints to be depicted in the
plot's legend. Should be a sequence from -1 to 1.
|
Examples
set.seed(42)
airq.ens <- pre(Ozone ~ ., data = airquality[complete.cases(airquality),])
corplot(airq.ens)
[Package
pre version 1.0.7
Index]