pdp: autoplot.partial – R documentation

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pdp

autoplot.partial

Plotting Partial Dependence Functions

Description

Plots partial dependence functions (i.e., marginal effects) using ggplot2 graphics.

Usage

## S3 method for class 'partial'
autoplot(object, center = FALSE, plot.pdp = TRUE,
  pdp.color = "red", pdp.size = 1, pdp.linetype = 1, rug = FALSE,
  smooth = FALSE, smooth.method = "auto", smooth.formula = y ~ x,
  smooth.span = 0.75, smooth.method.args = list(), contour = FALSE,
  contour.color = "white", palette = c("viridis", "magma", "inferno",
  "plasma", "cividis"), train = NULL, xlab = NULL, ylab = NULL,
  main = NULL, legend.title = "yhat", ...)

## S3 method for class 'ice'
autoplot(object, center = FALSE, plot.pdp = TRUE,
  pdp.color = "red", pdp.size = 1, pdp.linetype = 1, rug = FALSE,
  train = NULL, xlab = NULL, ylab = NULL, main = NULL, ...)

## S3 method for class 'cice'
autoplot(object, plot.pdp = TRUE, pdp.color = "red",
  pdp.size = 1, pdp.linetype = 1, rug = FALSE, train = NULL,
  xlab = NULL, ylab = NULL, main = NULL, ...)

Arguments

`object`	An object that inherits from the `"partial"` class.
`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.color`	Character string specifying the color to use for the partial dependence function when `plot.pdp = TRUE`. Default is `"red"`.
`pdp.size`	Positive number specifying the line width to use for the partial dependence function when `plot.pdp = TRUE`. Default is `1`.
`pdp.linetype`	Positive number specifying the line type to use for the partial dependence function when `plot.pdp = TRUE`. Default is `1`.
`rug`	Logical indicating whether or not to include rug marks on the predictor axes. Default is `FALSE`.
`smooth`	Logical indicating whether or not to overlay a LOESS smooth. Default is `FALSE`.
`smooth.method`	Character string specifying the smoothing method (function) to use (e.g., `"auto"`, `"lm"`, `"glm"`, `"gam"`, `"loess"`, or `"rlm"`). Default is `"auto"`. See `geom_smooth` for details.
`smooth.formula`	Formula to use in smoothing function (e.g., `y ~ x`, `y ~ poly(x, 2)`, or `y ~ log(x)`).
`smooth.span`	Controls the amount of smoothing for the default loess smoother. Smaller numbers produce wigglier lines, larger numbers produce smoother lines. Default is `0.75`.
`smooth.method.args`	List containing additional arguments to be passed on to the modeling function defined by `smooth.method`.
`contour`	Logical indicating whether or not to add contour lines to the level plot.
`contour.color`	Character string specifying the color to use for the contour lines when `contour = TRUE`. Default is `"white"`.
`palette`	Character string indicating the colormap option to use. Five options are available: "viridis" (the default), "magma", "inferno", "plasma", and "cividis".
`train`	Data frame containing the original training data. Only required if `rug = TRUE` or `chull = TRUE`.
`xlab`	Character string specifying the text for the x-axis label.
`ylab`	Character string specifying the text for the y-axis label.
`main`	Character string specifying the text for the main title of the plot.
`legend.title`	Character string specifying the text for the legend title. Default is `"yhat"`.
`...`	Additional optional arguments to be passed onto `geom_line`.

Value

A "ggplot" object.

Examples

## Not run: 
#
# Regression example (requires randomForest package to run)
#

# Load required packages
library(ggplot2)  # required to use autoplot
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") %>%
  autoplot(rug = TRUE, train = boston)

# Partial dependence of cmedv on lstat and rm
boston.rf %>%
  partial(pred.var = c("lstat", "rm"), chull = TRUE, progress = "text") %>%
  autoplot(contour = TRUE, legend.title = "rm")

# ICE curves and c-ICE curves
age.ice <- partial(boston.rf, pred.var = "lstat", ice = TRUE)
grid.arrange(
  autoplot(age.ice, alpha = 0.5),                 # ICE curves
  autoplot(age.ice, center = TRUE, alpha = 0.5),  # c-ICE curves
  ncol = 2
)

## End(Not run)

pdp

Partial Dependence Plots

v0.7.0

GPL (>= 2)

Authors

Brandon Greenwell [aut, cre] (<https://orcid.org/0000-0002-8120-0084>)

Initial release