Nirvana Distance

Versión 1.0.2 (2,08 KB) por David Heise
This code computes the nirvana distance, or distance from "ideal" for a data augmentation.
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Actualizado 20 ago 2023

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This function will calculate the nirvana distance -- that is, the distance from "ideal" -- for a data augmentation.
Inputs:
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
Outputs:
ND - the computed nirvana distance
dc - a vector of values representing the distance component for each target class in the data set

Citar como

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.

Compatibilidad con la versión de MATLAB
Se creó con R2023a
Compatible con cualquier versión
Compatibilidad con las plataformas
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Inspiración para: Plotting Components for Nirvana Distance

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Versión Publicado Notas de la versión
1.0.2

updated citation

1.0.1

corrected small (but fatal) errors

1.0.0