kmeans_opt

Version 1.0.0.1 (1,86 ko) par Sebastien De Landtsheer
tries k-means over different number of clusters
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Mise à jour 4 avr. 2019

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k-means is a decent clustering algorithm, however it requires the specification of the number of clusters, and is stochastic.
This function takes a matrix as input, as well as the maximum number of clusters, the cutoff to determine the best model (the fraction of variance explained), and makes sure the results are stable by repeating a number of times specified by the user.
The above method is called the Elbow method.

Citation pour cette source

Sebastien De Landtsheer (2024). kmeans_opt (https://www.mathworks.com/matlabcentral/fileexchange/65823-kmeans_opt), MATLAB Central File Exchange. Récupéré le .

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Créé avec R2017a
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Version Publié le Notes de version
1.0.0.1

New version as of 4th April 2019: unit-normalizes the variables, so the algo works even if the variables are on completely different styles.
1.0.0.0