This method creates precision-recall curves based on data in a familiarCollection object.
plot_auc_precision_recall_curve(
object,
draw = FALSE,
dir_path = NULL,
split_by = NULL,
color_by = NULL,
facet_by = NULL,
facet_wrap_cols = NULL,
ggtheme = NULL,
discrete_palette = NULL,
x_label = waiver(),
y_label = waiver(),
legend_label = waiver(),
plot_title = waiver(),
plot_sub_title = waiver(),
caption = NULL,
x_n_breaks = 5,
x_breaks = NULL,
y_n_breaks = 5,
y_breaks = NULL,
conf_int_style = c("ribbon", "step", "none"),
conf_int_alpha = 0.4,
width = waiver(),
height = waiver(),
units = waiver(),
export_collection = FALSE,
...
)# S4 method for ANY
plot_auc_precision_recall_curve(
object,
draw = FALSE,
dir_path = NULL,
split_by = NULL,
color_by = NULL,
facet_by = NULL,
facet_wrap_cols = NULL,
ggtheme = NULL,
discrete_palette = NULL,
x_label = waiver(),
y_label = waiver(),
legend_label = waiver(),
plot_title = waiver(),
plot_sub_title = waiver(),
caption = NULL,
x_n_breaks = 5,
x_breaks = NULL,
y_n_breaks = 5,
y_breaks = NULL,
conf_int_style = c("ribbon", "step", "none"),
conf_int_alpha = 0.4,
width = waiver(),
height = waiver(),
units = waiver(),
export_collection = FALSE,
...
)
# S4 method for familiarCollection
plot_auc_precision_recall_curve(
object,
draw = FALSE,
dir_path = NULL,
split_by = NULL,
color_by = NULL,
facet_by = NULL,
facet_wrap_cols = NULL,
ggtheme = NULL,
discrete_palette = NULL,
x_label = waiver(),
y_label = waiver(),
legend_label = waiver(),
plot_title = waiver(),
plot_sub_title = waiver(),
caption = NULL,
x_n_breaks = 5,
x_breaks = NULL,
y_n_breaks = 5,
y_breaks = NULL,
conf_int_style = c("ribbon", "step", "none"),
conf_int_alpha = 0.4,
width = waiver(),
height = waiver(),
units = waiver(),
export_collection = FALSE,
...
)
NULL
or list of plot objects, if dir_path
is NULL
.
familiarCollection
object, or one or more familiarData
objects, that will be internally converted to a familiarCollection
object. It is also possible to provide a familiarEnsemble
or one or more
familiarModel
objects together with the data from which data is computed
prior to export. Paths to such files can also be provided.
(optional) Draws the plot if TRUE.
(optional) Path to the directory where the plots of receiver
operating characteristic curves are saved to. Output is saved in the
performance
subdirectory. If NULL
no figures are saved, but are returned
instead.
(optional) Splitting variables. This refers to column names on which datasets are split. A separate figure is created for each split. See details for available variables.
(optional) Variables used to determine fill colour of plot
objects. The variables cannot overlap with those provided to the split_by
argument, but may overlap with other arguments. See details for available
variables.
(optional) Variables used to determine how and if facets of
each figure appear. In case the facet_wrap_cols
argument is NULL
, the
first variable is used to define columns, and the remaing variables are
used to define rows of facets. The variables cannot overlap with those
provided to the split_by
argument, but may overlap with other arguments.
See details for available variables.
(optional) Number of columns to generate when facet wrapping. If NULL, a facet grid is produced instead.
(optional) ggplot
theme to use for plotting.
(optional) Palette to use to color the different
plot elements in case a value was provided to the color_by
argument.
(optional) Label to provide to the x-axis. If NULL, no label is shown.
(optional) Label to provide to the y-axis. If NULL, no label is shown.
(optional) Label to provide to the legend. If NULL, the legend will not have a name.
(optional) Label to provide as figure title. If NULL, no title is shown.
(optional) Label to provide as figure subtitle. If NULL, no subtitle is shown.
(optional) Label to provide as figure caption. If NULL, no caption is shown.
(optional) Number of breaks to show on the x-axis of the
plot. x_n_breaks
is used to determine the x_breaks
argument in case it
is unset.
(optional) Break points on the x-axis of the plot.
(optional) Number of breaks to show on the y-axis of the
plot. y_n_breaks
is used to determine the y_breaks
argument in case it
is unset.
(optional) Break points on the y-axis of the plot.
(optional) Confidence interval style. See details for allowed styles.
(optional) Alpha value to determine transparency of confidence intervals or, alternatively, other plot elements with which the confidence interval overlaps. Only values between 0.0 (fully transparent) and 1.0 (fully opaque) are allowed.
(optional) Width of the plot. A default value is derived from the number of facets.
(optional) Height of the plot. A default value is derived from the number of features and the number of facets.
(optional) Plot size unit. Either cm
(default), mm
or
in
.
(optional) Exports the collection if TRUE.
Arguments passed on to as_familiar_collection
, ggplot2::ggsave
familiar_data_names
Names of the dataset(s). Only used if the object
parameter is one or more familiarData
objects.
collection_name
Name of the collection.
device
Device to use. Can either be a device function
(e.g. png), or one of "eps", "ps", "tex" (pictex),
"pdf", "jpeg", "tiff", "png", "bmp", "svg" or "wmf" (windows only). If
NULL
(default), the device is guessed based on the filename
extension.
scale
Multiplicative scaling factor.
dpi
Plot resolution. Also accepts a string input: "retina" (320), "print" (300), or "screen" (72). Applies only to raster output types.
limitsize
When TRUE
(the default), ggsave()
will not
save images larger than 50x50 inches, to prevent the common error of
specifying dimensions in pixels.
bg
Background colour. If NULL
, uses the plot.background
fill value
from the plot theme.
create.dir
Whether to create new directories if a non-existing
directory is specified in the filename
or path
(TRUE
) or return an
error (FALSE
, default). If FALSE
and run in an interactive session,
a prompt will appear asking to create a new directory when necessary.
This function generates area under the precision-recall curve plots.
Available splitting variables are: fs_method
, learner
, data_set
and
positive_class
. By default, the data is split by fs_method
and learner
,
with faceting by data_set
and colouring by positive_class
.
Available palettes for discrete_palette
are those listed by
grDevices::palette.pals()
(requires R >= 4.0.0), grDevices::hcl.pals()
(requires R >= 3.6.0) and rainbow
, heat.colors
, terrain.colors
,
topo.colors
and cm.colors
, which correspond to the palettes of the same
name in grDevices
. If not specified, a default palette based on palettes
in Tableau are used. You may also specify your own palette by using colour
names listed by grDevices::colors()
or through hexadecimal RGB strings.
Bootstrap confidence intervals of the ROC curve (if present) can be shown
using various styles set by conf_int_style
:
ribbon
(default): confidence intervals are shown as a ribbon with an
opacity of conf_int_alpha
around the point estimate of the ROC curve.
step
(default): confidence intervals are shown as a step function around
the point estimate of the ROC curve.
none
: confidence intervals are not shown. The point estimate of the ROC
curve is shown as usual.
Labelling methods such as set_fs_method_names
or set_data_set_names
can
be applied to the familiarCollection
object to update labels, and order
the output in the figure.