1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105
|
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/plotBMRRanksAsBarChart.R
\name{plotBMRRanksAsBarChart}
\alias{plotBMRRanksAsBarChart}
\title{Create a bar chart for ranks in a BenchmarkResult.}
\usage{
plotBMRRanksAsBarChart(
bmr,
measure = NULL,
ties.method = "average",
aggregation = "default",
pos = "stack",
order.lrns = NULL,
order.tsks = NULL,
pretty.names = TRUE
)
}
\arguments{
\item{bmr}{(\link{BenchmarkResult})\cr
Benchmark result.}
\item{measure}{(\link{Measure})\cr
Performance measure.
Default is the first measure used in the benchmark experiment.}
\item{ties.method}{(\code{character(1)})\cr
See \link{rank} for details.}
\item{aggregation}{(\code{character(1)}) \cr
\dQuote{mean} or \dQuote{default}. See \link{getBMRAggrPerformances}
for details on \dQuote{default}.}
\item{pos}{(\code{character(1)})\cr
Optionally set how the bars are positioned in ggplot2.
Ranks are plotted on the x-axis.
\dQuote{tile} plots a heat map with \code{task} as the y-axis.
Allows identification of the performance in a special task.
\dQuote{stack} plots a stacked bar plot.
Allows for comparison of learners within and and across ranks.
\dQuote{dodge} plots a bar plot with bars next to each other instead
of stacked bars.}
\item{order.lrns}{(\code{character(n.learners)})\cr
Character vector with \code{learner.ids} in new order.}
\item{order.tsks}{(\code{character(n.tasks)})\cr
Character vector with \code{task.ids} in new order.}
\item{pretty.names}{(\code{logical(1)})\cr
Whether to use the short name of the learner instead of its ID in labels. Defaults to \code{TRUE}.}
}
\value{
ggplot2 plot object.
}
\description{
Plots a bar chart from the ranks of algorithms. Alternatively,
tiles can be plotted for every rank-task combination, see \code{pos}
for details. In all plot variants the ranks of the learning algorithms are displayed on
the x-axis. Areas are always colored according to the \code{learner.id}.
}
\examples{
# see benchmark
}
\seealso{
Other plot:
\code{\link{createSpatialResamplingPlots}()},
\code{\link{plotBMRBoxplots}()},
\code{\link{plotBMRSummary}()},
\code{\link{plotCalibration}()},
\code{\link{plotCritDifferences}()},
\code{\link{plotLearningCurve}()},
\code{\link{plotPartialDependence}()},
\code{\link{plotROCCurves}()},
\code{\link{plotResiduals}()},
\code{\link{plotThreshVsPerf}()}
Other benchmark:
\code{\link{BenchmarkResult}},
\code{\link{batchmark}()},
\code{\link{benchmark}()},
\code{\link{convertBMRToRankMatrix}()},
\code{\link{friedmanPostHocTestBMR}()},
\code{\link{friedmanTestBMR}()},
\code{\link{generateCritDifferencesData}()},
\code{\link{getBMRAggrPerformances}()},
\code{\link{getBMRFeatSelResults}()},
\code{\link{getBMRFilteredFeatures}()},
\code{\link{getBMRLearnerIds}()},
\code{\link{getBMRLearnerShortNames}()},
\code{\link{getBMRLearners}()},
\code{\link{getBMRMeasureIds}()},
\code{\link{getBMRMeasures}()},
\code{\link{getBMRModels}()},
\code{\link{getBMRPerformances}()},
\code{\link{getBMRPredictions}()},
\code{\link{getBMRTaskDescs}()},
\code{\link{getBMRTaskIds}()},
\code{\link{getBMRTuneResults}()},
\code{\link{plotBMRBoxplots}()},
\code{\link{plotBMRSummary}()},
\code{\link{plotCritDifferences}()},
\code{\link{reduceBatchmarkResults}()}
}
\concept{benchmark}
\concept{plot}
|