plotBMRRanksAsBarChart: Create a bar chart for ranks in a BenchmarkResult.
In Najah-lshanableh/R-data-mining2: Machine Learning in R

Description Usage Arguments Value See Also Examples

Plots a bar chart from the ranks of algorithms. Alternatively, tiles can be plotted for every rank-task combination, see 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 learner.id.

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plotBMRRanksAsBarChart(bmr, measure = NULL, ties.method = "average",
  aggregation = "default", pos = "stack", order.lrns = NULL,
  order.tsks = NULL, pretty.names = TRUE)

`bmr`	[`BenchmarkResult`] Benchmark result.
`measure`	[`Measure`] Performance measure. Default is the first measure used in the benchmark experiment.
`ties.method`	[`character(1)`] See `rank` for details.
`aggregation`	[`character(1)`] “mean” or “default”. See `getBMRAggrPerformances` for details on “default”.
`pos`	[`character(1)`] Optionally set how the bars are positioned in ggplot2. Ranks are plotted on the x-axis. “tile” plots a heat map with `task` as the y-axis. Allows identification of the performance in a special task. “stack” plots a stacked bar plot. Allows for comparison of learners within and and across ranks. “dodge” plots a bar plot with bars next to each other instead of stacked bars.
`order.lrns`	[`character(n.learners)`] Character vector with `learner.ids` in new order.
`order.tsks`	[`character(n.tasks)`] Character vector with `task.ids` in new order.
`pretty.names`	[`logical{1}`] Whether to use the short name of the learner instead of its ID in labels. Defaults to `TRUE`.