plotPartial function

Plotting Partial Dependence Functions

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,
  ...
)

Arguments

• object: An object that inherits from the "partial" class.

• ...: Additional optional arguments to be passed onto dotplot, levelplot, xyplot, or wireframe.

• center: Logical indicating whether or not to produce centered ICE curves (c-ICE curves). Only useful when object represents a set of ICE curves; see partial for details. Default is FALSE.

• plot.pdp: Logical indicating whether or not to plot the partial dependence function on top of the ICE curves. Default is TRUE.

• pdp.col: Character string specifying the color to use for the partial dependence function when plot.pdp = TRUE. Default is "red".

• pdp.lwd: Integer specifying the line width to use for the partial dependence function when plot.pdp = TRUE. Default is 1. See par for more details.

• pdp.lty: Integer or character string specifying the line type to use for the partial dependence function when plot.pdp = TRUE. Default is 1. See par for more details.

• rug: Logical indicating whether or not to include rug marks on the predictor axes. Default is FALSE.

• train: Data frame containing the original training data. Only required if rug = TRUE or chull = TRUE.

• smooth: Logical indicating whether or not to overlay a LOESS smooth. Default is FALSE.

• chull: Logical indicating whether or not to restrict the first two variables in pred.var to lie within the convex hull of their training values; this affects pred.grid. Default is FALSE.

• levelplot: Logical indicating whether or not to use a false color level plot (TRUE) or a 3-D surface (FALSE). Default is TRUE.

• contour: Logical indicating whether or not to add contour lines to the level plot. Only used when levelplot = TRUE. Default is FALSE.

• contour.color: Character string specifying the color to use for the contour lines when contour = TRUE. Default is "white".

• col.regions: Vector of colors to be passed on to levelplot's col.region argument. Defaults to grDevices::hcl.colors(100) (which is the same viridis color palette used in the past).

• number: Integer specifying the number of conditional intervals to use for the continuous panel variables. See co.intervals

  and equal.count for further details.

• overlap: The fraction of overlap of the conditioning variables. See co.intervals and equal.count

  for further details.

Examples

## 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)