PCA for dimension reduction in 1D data

Versione 1.0.0 (2,05 KB) da Selva
using principal component analysis for dimension reduction of feature vector in the SVM classification problem
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Aggiornato 28 set 2018

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PCA is used for projecting data matrix from higher dimension to lower dimension

Cita come

Selva (2024). PCA for dimension reduction in 1D data (https://www.mathworks.com/matlabcentral/fileexchange/68942-pca-for-dimension-reduction-in-1d-data), MATLAB Central File Exchange. Recuperato .

Compatibilità della release di MATLAB
Creato con R2018b
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Versione Pubblicato Note della release
1.0.0