Crossfold Validation Performance Plot.

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Description

Compares the performance of each algorithm in a boxplot OR barplot. Each holdout will contribute at least one data point to each algorithm.

Usage

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cv.plot(obj, metric = "AUROC", y_ranges = c(0, 1), title = "",
  type = "boxplot")

Arguments

obj

An object produced by the blkboxCV function.

metric

Which metric you wish to plot. Area under the Receiver operating curve = "AUROC", Accuracy = "ACC", Error rate = "ERR", Matthews correlation coefficient = "MCC", F-1 score = "F-1". default = c("AUROC")

y_ranges

is the y axis limits for the plot, defaults to c(0,1). Must be a numeric vector with two entries. Invalid for barplots.

title

the title to be adhered to the plot. Default is no title.

type

The plot can be either a barplot or boxplot. For the barplot the consensus performance is used, for a boxplot consensus is false. If only one performance measure is found for each algorithm then it will be forced to a barplot. default = "boxplot", unless data is unsupported.

Author(s)

Zachary Davies, Boris Guennewig

Examples

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cv.plot(blkboxCV(...), metric = "AUROC", title = "Example Performance Barplot")