plot.ice: Plotting of 'ice' objects.

In ICEbox: Individual Conditional Expectation Plot Toolbox

Plotting of ice objects.

Description

Plotting of ice objects.

Usage

## S3 method for class 'ice'
plot(x, plot_margin = 0.05, frac_to_plot = 1, 
	 plot_points_indices = NULL, plot_orig_pts_preds = TRUE, 
     pts_preds_size = 1.5, colorvec, color_by = NULL, 
     x_quantile = TRUE, plot_pdp = TRUE,
     centered = FALSE, prop_range_y = TRUE, 
     rug_quantile = seq(from = 0, to = 1, by = 0.1),
     centered_percentile = 0, 
     point_labels = NULL, point_labels_size = NULL, 
     prop_type,...)

Arguments

x	Object of class ice to plot.
plot_margin	Extra margin to pass to ylim as a fraction of the range of x$ice_curves.
frac_to_plot	If frac_to_plot is less than 1, randomly plot frac_to_plot fraction of the curves in x$ice_curves.
plot_points_indices	If not NULL, this plots only the indices of interest. If not NULL, frac_to_plot must be 1 otherwise an error is thrown. Default is NULL.
plot_orig_pts_preds	If TRUE, marks each curve at the location of the observation's actual fitted value. If FALSE, no mark is drawn.
pts_preds_size	Size of points to make if plot_origin_pts_preds is TRUE.
colorvec	Optional vector of colors to use for each curve.
color_by	Optional variable name in Xice, column number in Xice, or data vector of the correct length to color curves by. If the color_by variable has 10 or fewer unique values, a discrete set of colors is used for each value and a legend is printed and returned. If there are more values, curves are colored from light to dark corresponding to low to high values of the variable specified by color_by.
x_quantile	If TRUE, the plot is drawn with the x-axis taken to be quantile(gridpts). If FALSE, the predictor's original scale is used.
plot_pdp	If TRUE, the PDP is plotted and highlighted in yellow.
centered	If TRUE, all curves are re-centered to be 0 at the quantile given by centered_percentile. See Goldstein et al (2013) for details and examples. If FALSE, the original ice_curves are plotted.
prop_range_y	When TRUE and centered=TRUE as well, the range of the right vertical axis displays the centered values as a fraction of the sd of the fitted values on actual observations if prop_type is missing or set to "sd". If prop_type is set to "range", the right axis displays the centered values as a fraction of the range of the fitted values over the actual observations.
centered_percentile	The percentile of predictor for which all ice_curves are "pinched together" and set to be 0. Default is .01.
point_labels	If not NULL, labels to plot next to each point. Default is NULL.
point_labels_size	If not NULL, size of labels to plot next to each point. Default is NULL which means it's the size of pts_preds_size.
rug_quantile	If not NULL, tick marks are drawn on the x-axis corresponding to the vector of quantiles specified by this parameter. Forced to NULL when x_quantile is set to TRUE.
prop_type	Scaling factor for the right vertical axis in centered plots if prop_range_y is TRUE. Can be one of "sd" (default) or "range". Ignored if centered and prop_range_y are not both TRUE.
...	Other arguments to be passed to the plot function.

Value

A list with the following elements.

plot_points_indices	Row numbers of Xice of those observations presented in the plot.
legend_text	If the color_by argument was used, a legend describing the map between the color_by predictor and curve colors.

See Also

ice

Examples

## Not run: 
require(ICEbox)
require(randomForest)
require(MASS) #has Boston Housing data, Pima

data(Boston) #Boston Housing data
X = Boston
y = X$medv
X$medv = NULL

## build a RF:
bhd_rf_mod = randomForest(X, y)

## Create an 'ice' object for the predictor "age":
bhd.ice = ice(object = bhd_rf_mod, X = X, y = y, predictor = "age",
            frac_to_build = .1) 

## plot
plot(bhd.ice, x_quantile = TRUE, plot_pdp = TRUE, frac_to_plot = 1) 

## centered plot
plot(bhd.ice, x_quantile = TRUE, plot_pdp = TRUE, frac_to_plot = 1, 
		centered = TRUE) 

## color the curves by high and low values of 'rm'.
# First create an indicator variable which is 1 if the number of 
# rooms is greater than the median:
median_rm = median(X$rm)
bhd.ice$Xice$I_rm = ifelse(bhd.ice$Xice$rm > median_rm, 1, 0)  

plot(bhd.ice, frac_to_plot = 1, centered = TRUE, prop_range_y = TRUE,  
            x_quantile = T, plot_orig_pts_preds = T, color_by = "I_rm")
bhd.ice = ice(object = bhd_rf_mod, X = X, y = y, predictor = "age",
            frac_to_build = 1)             
plot(bhd.ice, frac_to_plot = 1, centered = TRUE, prop_range_y = TRUE,  
            x_quantile = T, plot_orig_pts_preds = T, color_by = y)            

## End(Not run)

ICEbox documentation built on Aug. 22, 2022, 5:05 p.m.