plot.rm_confusion_matrix {NeuroDecodeR}R Documentation

A plot function for the rm_confusion_matrix object

Description

This function plots confusion matrices after the decoding analysis has been run (and all results have been aggregated). This function can also plot mutual information calculated from the confusion matrix.

Usage

## S3 method for class 'rm_confusion_matrix'
plot(
  x,
  ...,
  results_to_show = "zero_one_loss",
  plot_TCD_results = FALSE,
  plot_only_one_train_time = NULL
)

Arguments

x

A rm_confusion_matrix object that has aggregated runs from a decoding analysis, e.g., if DECODING_RESULTS are the output from the run_decoding(cv) then this argument should be DECODING_RESULTS$rm_confusion_matrix.

...

This is needed to conform to the plot generic interface.

results_to_show

A string specifying the type of result to plot that can take the following values:

  • "zero_one_loss": plot a regular confusion matrix.

  • "decision_vals": plot a confusion matrix with the average decision values.

  • "mutual_information": plot the mutual information calculated from the zero-one loss confusion matrix.

plot_TCD_results

A Boolean indicating whether the a cross-temporal decoding of the confusion matrices should only be plotted. If the results_to_show == "mutual_information" setting this to TRUE will plot a TCD plot of the mutual information otherwise it will plot a line plot of the mutual information for training and testing at the same time.

plot_only_one_train_time

If this is set to a numeric value the the confusion matrix will only be plotted for the training time start time that is specified. If the number passed is not equal to an exact start training time, then the closest training time will be used and a message saying that the time specified does not exist will be printed.

Value

Returns a ggplot object that plots the confusion matrix results.

See Also

Other result_metrics: plot.rm_main_results(), plot_main_results(), rm_confusion_matrix(), rm_main_results()


[Package NeuroDecodeR version 0.2.0 Index]