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ICEbox

plot.ice

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 = FALSE, 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.

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

Individual Conditional Expectation Plot Toolbox

v1.1.2

GPL-2 | GPL-3

Authors

Alex Goldstein, Adam Kapelner, Justin Bleich

Initial release

2017-07-12

plot.ice

Description

Usage

Arguments

Value

See Also

Examples

ICEbox

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