This function updates the options of a modelStudio object. WARNING: Editing default options may cause unintended behavior.

ms_update_options(object, ...)

Arguments

object

A modelStudio created with modelStudio().

...

Options to change in the form option_name = value, e.g. time = 0, facet_dim = c(1,2).

Value

An object of the r2d3, htmlwidget, modelStudio class.

Options

Main options:

scale_plot

TRUE Makes every plot the same height, ignores bar_width.

show_boxplot

TRUE Display boxplots in Feature Importance and Shapley Values plots.

show_subtitle

TRUE Should the subtitle be displayed?

subtitle

label parameter from explainer.

ms_title

Title of the dashboard.

ms_subtitle

Subtitle of the dashboard (makes space between the title and line).

ms_margin_*

Dashboard margins. Change margin_top for more ms_subtitle space.

margin_*

Plot margins. Change margin_left for longer/shorter axis labels.

w

420 in px. Inner plot width.

h

280 in px. Inner plot height.

bar_width

16 in px. Default width of bars for all plots, ignored when scale_plot = TRUE.

line_size

2 in px. Default width of lines for all plots.

point_size

3 in px. Default point radius for all plots.

[bar,line,point]_color

[#46bac2,#46bac2,#371ea3]

positive_color

#8bdcbe for Break Down and Shapley Values bars.

negative_color

#f05a71 for Break Down and Shapley Values bars.

default_color

#371ea3 for Break Down bar and highlighted line.

Plot specific options:

** is a two letter code unique to each plot, might be one of [bd,sv,cp,fi,pd,ad,rv,fd,tv,at].

**_title

Plot specific title. Default varies.

**_subtitle

Plot specific subtitle. Default is subtitle.

**_bar_width

Plot specific width of bars. Default is bar_width, ignored when scale_plot = TRUE.

**_line_size

line_size Plot specific width of lines. Default is line_size.

**_point_size

Plot specific point radius. Default is point_size.

**_*_color

Plot specific [bar,line,point] color. Default is [bar,line,point]_color.

References

  • The input object is implemented in DALEX

  • Feature Importance, Ceteris Paribus, Partial Dependence and Accumulated Dependence explanations are implemented in ingredients

  • Break Down and Shapley Values explanations are implemented in iBreakDown

See also

Examples

library("DALEX") library("modelStudio") # fit a model model_titanic <- glm(survived ~., data = titanic_imputed, family = "binomial") # create an explainer for the model explainer_titanic <- explain(model_titanic, data = titanic_imputed, y = titanic_imputed$survived)
#> Preparation of a new explainer is initiated #> -> model label : lm ( default ) #> -> data : 2207 rows 8 cols #> -> target variable : 2207 values #> -> predict function : yhat.glm will be used ( default ) #> -> predicted values : No value for predict function target column. ( default ) #> -> model_info : package stats , ver. 4.0.5 , task classification ( default ) #> -> predicted values : numerical, min = 0.008128381 , mean = 0.3221568 , max = 0.9731431 #> -> residual function : difference between y and yhat ( default ) #> -> residuals : numerical, min = -0.9628583 , mean = -2.569729e-10 , max = 0.9663346 #> A new explainer has been created!
# make a studio for the model ms <- modelStudio(explainer_titanic, N = 200, B = 5) # faster example
#> `new_observation` argument is NULL. `new_observation_n` observations needed to calculate local explanations are taken from the data.
# update the options new_ms <- ms_update_options(ms, time = 0, facet_dim = c(1,2), margin_left = 150) new_ms