autoplot.partial: Plotting Partial Dependence Functions In pdp: Partial Dependence Plots

Description

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

Usage

 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 ## 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

 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 ## 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 documentation built on May 1, 2019, 9:20 p.m.