HyperParsEffectData
object. Useful for determining the importance
or effect of a particular hyperparameter on some performance measure and/or
optimizer.
plotHyperParsEffect(hyperpars.effect.data, x = NULL, y = NULL, z = NULL, plot.type = "scatter", loess.smooth = FALSE, facet = NULL, pretty.names = TRUE, global.only = TRUE, interpolate = NULL, show.experiments = FALSE, show.interpolated = FALSE, nested.agg = mean)
HyperParsEffectData
]
Result of generateHyperParsEffectData
character(1)
]
Specify what should be plotted on the x axis. Must be a column from
HyperParsEffectData$data
character(1)
]
Specify what should be plotted on the y axis. Must be a column from
HyperParsEffectData$data
character(1)
]
Specify what should be used as the extra axis for a particular geom. This
could be for the fill on a heatmap or color aesthetic for a line. Must be a
column from HyperParsEffectData$data
. Default is NULL
.character(1)
]
Specify the type of plot: scatter for a scatterplot, heatmap for a
heatmap, line for a scatterplot with a connecting line, or contour for a
contour plot layered ontop of a heatmap.
Default is scatter.logical(1)
]
If TRUE
, will add loess smoothing line to plots where possible. Note that
this is probably only useful when plot.type
is set to either
scatter or line. Must be a column from HyperParsEffectData$data
Default is FALSE
.character(1)
]
Specify what should be used as the facet axis for a particular geom. When
using nested cross validation, set this to nested_cv_run to obtain a facet
for each outer loop. Must be a column from HyperParsEffectData$data
Default is NULL
.logical{1}
]
Whether to use the short name of the learner instead of its ID in labels. Defaults to TRUE
.logical(1)
]
If TRUE
, will only plot the current global optima when setting
x = "iteration" and y as a performance measure from
HyperParsEffectData$measures
. Set this to FALSE to always plot the
performance of every iteration, even if it is not an improvement.
Default is TRUE
.Learner
| character(1)
]
If not NULL
, will interpolate non-complete grids in order to visualize a more
complete path. Only meaningful when attempting to plot a heatmap or contour.
This will fill in empty cells in the heatmap or contour plot. Note that
cases of irregular hyperparameter paths, you will most likely need to use
this to have a meaningful visualization. Accepts either a Learner
object or the learner as a string for interpolation.
Default is NULL
.logical(1)
]
If TRUE
, will overlay the plot with points indicating where an experiment
ran. This is only useful when creating a heatmap or contour plot with
interpolation so that you can see which points were actually on the
original path. Note: if any learner crashes occurred within the path, this
will become TRUE
.
Default is FALSE
.logical(1)
]
If TRUE
, will overlay the plot with points indicating where interpolation
ran. This is only useful when creating a heatmap or contour plot with
interpolation so that you can see which points were interpolated.
Default is FALSE
.function
]
The function used to aggregate nested cross validation runs when plotting 2
hyperpars simultaneously. This is only useful when nested cross validation
is used along with plotting a 2 hyperpars.
Default is mean
.# see generateHyperParsEffectData
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