plotPartial | R Documentation |
Plots partial dependence functions (i.e., marginal effects) using
lattice
graphics.
plotPartial(object, ...)
## S3 method for class 'ice'
plotPartial(
object,
center = FALSE,
plot.pdp = TRUE,
pdp.col = "red2",
pdp.lwd = 2,
pdp.lty = 1,
rug = FALSE,
train = NULL,
...
)
## S3 method for class 'cice'
plotPartial(
object,
plot.pdp = TRUE,
pdp.col = "red2",
pdp.lwd = 2,
pdp.lty = 1,
rug = FALSE,
train = NULL,
...
)
## S3 method for class 'partial'
plotPartial(
object,
center = FALSE,
plot.pdp = TRUE,
pdp.col = "red2",
pdp.lwd = 2,
pdp.lty = 1,
smooth = FALSE,
rug = FALSE,
chull = FALSE,
levelplot = TRUE,
contour = FALSE,
contour.color = "white",
col.regions = NULL,
number = 4,
overlap = 0.1,
train = NULL,
...
)
object |
An object that inherits from the |
... |
Additional optional arguments to be passed onto |
center |
Logical indicating whether or not to produce centered ICE
curves (c-ICE curves). Only useful when |
plot.pdp |
Logical indicating whether or not to plot the partial
dependence function on top of the ICE curves. Default is |
pdp.col |
Character string specifying the color to use for the partial
dependence function when |
pdp.lwd |
Integer specifying the line width to use for the partial
dependence function when |
pdp.lty |
Integer or character string specifying the line type to use
for the partial dependence function when |
rug |
Logical indicating whether or not to include rug marks on the
predictor axes. Default is |
train |
Data frame containing the original training data. Only required
if |
smooth |
Logical indicating whether or not to overlay a LOESS smooth.
Default is |
chull |
Logical indicating whether or not to restrict the first two
variables in |
levelplot |
Logical indicating whether or not to use a false color level
plot ( |
contour |
Logical indicating whether or not to add contour lines to the
level plot. Only used when |
contour.color |
Character string specifying the color to use for the
contour lines when |
col.regions |
Vector of colors to be passed on to
|
number |
Integer specifying the number of conditional intervals to use
for the continuous panel variables. See |
overlap |
The fraction of overlap of the conditioning variables. See
|
## Not run:
#
# Regression example (requires randomForest package to run)
#
# Load required packages
library(gridExtra) # for `grid.arrange()`
library(magrittr) # for forward pipe operator `%>%`
library(randomForest)
# Fit a random forest to the Boston housing data
data (boston) # load the boston housing data
set.seed(101) # for reproducibility
boston.rf <- randomForest(cmedv ~ ., data = boston)
# Partial dependence of cmedv on lstat
boston.rf %>%
partial(pred.var = "lstat") %>%
plotPartial(rug = TRUE, train = boston)
# Partial dependence of cmedv on lstat and rm
boston.rf %>%
partial(pred.var = c("lstat", "rm"), chull = TRUE, progress = TRUE) %>%
plotPartial(contour = TRUE, legend.title = "rm")
# ICE curves and c-ICE curves
age.ice <- partial(boston.rf, pred.var = "lstat", ice = TRUE)
p1 <- plotPartial(age.ice, alpha = 0.1)
p2 <- plotPartial(age.ice, center = TRUE, alpha = 0.1)
grid.arrange(p1, p2, ncol = 2)
## End(Not run)
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