cluster_distance

Version 1.0.0 (1.72 KB) by Joris Meurs
Assessment of class separation for partial-least squares discriminant analysis or principal component analysis using Hotelling's T2.
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Updated 10 Feb 2021

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Assessment of class separation for partial-least squares discriminant
analysis or principal component analysis using Hotelling's T2.

Input
data: N x M matrix with N samples and M variables
classVec: N x 1 vector with numeric class labels

Reference
A. M. Goodpaster, M. A. Kennedy, Chemom. Intell. Lab. Syst. 109, 162–170 (2011).

Cite As

Joris Meurs (2026). cluster_distance (https://www.mathworks.com/matlabcentral/fileexchange/87247-cluster_distance), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2020b
Compatible with any release
Platform Compatibility
Windows macOS Linux
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Version Published Release Notes
1.0.0