Nirvana Distance

Version 1.0.2 (2.08 KB) by David Heise
This code computes the nirvana distance, or distance from "ideal" for a data augmentation.
Updated 20 Aug 2023

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This function will calculate the nirvana distance -- that is, the distance from "ideal" -- for a data augmentation.
C - an integer matrix of the confusion data for the augmentation under evaluation, with ground truth labels in rows and predicted labels in columns
F - a square matrix representing the distances between target classes in the original (non-augmented) data feature space, with order of classes as in C
ND - the computed nirvana distance
dc - a vector of values representing the distance component for each target class in the data set

Cite As

D. Heise and H. Bear, "Evaluating the Potential and Realized Impact of Data Augmentations", submitted to 2023 IEEE Symposium Series on Computational Intelligence, in review.

MATLAB Release Compatibility
Created with R2023a
Compatible with any release
Platform Compatibility
Windows macOS Linux
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Inspired: Plotting Components for Nirvana Distance

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Version Published Release Notes

updated citation


corrected small (but fatal) errors