Plot prediction error according to various metrics.
Source:R/visualizer-lib-prediction.R
plot_pred_err.Rd
Plot the raw or summarized prediction errors as a boxplot, scatter plot, line plot, or bar plot with or without 1 SD error bars.
Usage
plot_pred_err(
fit_results = NULL,
eval_results = NULL,
eval_name = NULL,
eval_fun = "summarize_pred_err",
eval_fun_options = NULL,
vary_params = NULL,
metrics = NULL,
show = c("point", "line"),
...
)
Arguments
- fit_results
A tibble, as returned by
fit_experiment()
.- eval_results
A list of result tibbles, as returned by
evaluate_experiment()
.- eval_name
Name of
Evaluator
containing results to plot. IfNULL
, the data used for plotting is computed from scratch viaeval_fun
.- eval_fun
Character string, specifying the function used to compute the data used for plotting if
eval_name = NULL
. Ifeval_name
is notNULL
, this argument is ignored.- eval_fun_options
List of named arguments to pass to
eval_fun
.- vary_params
A vector of
DGP
orMethod
parameter names that are varied across in theExperiment
.- metrics
A
metric_set
object indicating the metrics to plot. Seeyardstick::metric_set()
for more details. DefaultNULL
will use the default metrics inyardstick::metrics()
.- show
Character vector with elements being one of "boxplot", "point", "line", "bar", "errorbar", "ribbon", "violin", indicating what plot layer(s) to construct.
- ...
Arguments passed on to
plot_eval_constructor
eval_id
(Optional) Character string. ID used as the suffix for naming columns in evaluation results tibble. If
eval_summary_constructor()
was used to construct theEvaluator
, this should be the same as theeval_id
argument ineval_summary_constructor()
. Only used to assign default (i.e., "auto") aesthetics in ggplot.x_str
(Optional) Name of column in data frame to plot on the x-axis. Default "auto" chooses what to plot on the x-axis automatically.
y_str
(Optional) Name of column in data frame to plot on the y-axis if
show
is anything but "boxplot". Default "auto" chooses what to plot on the y-axis automatically.y_boxplot_str
(Optional) Name of column in data frame to plot on the y-axis if
show
is "boxplot". Default "auto" chooses what to plot on the y-axis automatically.err_sd_str
(Optional) Name of column in data frame containing the standard deviations of
y_str
. Used for plotting the errorbar and ribbon ggplot layers. Default "auto" chooses what column to use for the standard deviations automatically.color_str
(Optional) Name of column in data frame to use for the color and fill aesthetics when plotting. Default "auto" chooses what to use for the color and fill aesthetics automatically. Use
NULL
to avoid adding any color and fill aesthetic.linetype_str
(Optional) Name of column in data frame to use for the linetype aesthetic when plotting. Used only when
show = "line"
. Default "auto" chooses what to use for the linetype aesthetic automatically. UseNULL
to avoid adding any linetype aesthetic.facet_formula
(Optional) Formula for
ggplot2::facet_wrap()
orggplot2::facet_grid()
if need be.facet_type
One of "grid" or "wrap" specifying whether to use
ggplot2::facet_wrap()
orggplot2::facet_grid()
if need be.plot_by
(Optional) Name of column in
eval_tib
to use for subsetting data and creating different plots for each unique value. Default "auto" chooses what column to use for the subsetting automatically. UseNULL
to avoid creating multiple plots.add_ggplot_layers
List of additional layers to add to a ggplot object via
+
.boxplot_args
(Optional) Additional arguments to pass into
ggplot2::geom_boxplot()
.point_args
(Optional) Additional arguments to pass into
ggplot2::geom_point()
.line_args
(Optional) Additional arguments to pass into
ggplot2::geom_line()
.bar_args
(Optional) Additional arguments to pass into
ggplot2::geom_bar()
.errorbar_args
(Optional) Additional arguments to pass into
ggplot2::geom_errorbar()
.ribbon_args
(Optional) Additional arguments to pass into
ggplot2::geom_ribbon()
.violin_args
(Optional) Additional arguments to pass into
ggplot2::geom_violin()
.facet_args
(Optional) Additional arguments to pass into
ggplot2::facet_grid()
orggplot2::facet_wrap()
.interactive
Logical. If
TRUE
, returns interactiveplotly
plots. IfFALSE
, returns staticggplot
plots.
Value
If interactive = TRUE
, returns a plotly
object if
plot_by
is NULL
and a list of plotly
objects if
plot_by
is not NULL
. If interactive = FALSE
, returns
a ggplot
object if plot_by
is NULL
and a list of
ggplot
objects if plot_by
is not NULL
.
See also
Other prediction_error_funs:
eval_pred_curve_funs
,
eval_pred_err_funs
,
plot_pred_curve()
Examples
# generate example fit_results data
fit_results <- tibble::tibble(
.rep = rep(1:2, times = 2),
.dgp_name = c("DGP1", "DGP1", "DGP2", "DGP2"),
.method_name = c("Method"),
# true response
y = lapply(1:4, FUN = function(x) rnorm(100)),
# predicted response
predictions = lapply(1:4, FUN = function(x) rnorm(100))
)
# generate example eval_results data
eval_results <- list(
`Prediction Errors` = summarize_pred_err(
fit_results, truth_col = "y", estimate_col = "predictions"
)
)
# create errorbar plot using pre-computed evaluation results
plt <- plot_pred_err(eval_results = eval_results,
eval_name = "Prediction Errors",
show = c("point", "errorbar"))
# or alternatively, create the same plot directly from fit results
plt <- plot_pred_err(fit_results = fit_results,
show = c("point", "errorbar"),
eval_fun_options = list(truth_col = "y",
estimate_col = "predictions"))
# can customize plot (see plot_eval_constructor() for possible arguments)
plt <- plot_pred_err(fit_results = fit_results, eval_results = eval_results,
eval_name = "Prediction Errors",
show = c("point", "errorbar"),
color_str = NULL,
facet_formula = .method_name ~ .metric,
facet_type = "grid")