using 'als' algorithm in pca
3 visualizaciones (últimos 30 días)
Mostrar comentarios más antiguos
I am doing PCA using 'als' algorithm as below. When I specify a specific number of components (1 here), the 'explained' term gives 100% as explained variance. How is it possible? Shouldn't be there more than one components as I have more than 1 variables? Shouldn't the explained give the percentage of variance explained by the first component only?
However, When I use 'eig' as the algorithm, it gives the percentage variance explained by each components, which I expected. Could someone explain this?
[COEFF, SCORE, latent, tsquared, explained, mu1] = pca (combined_aod_wind_raw, 'Centered', 'off', 'numcomponents', 1, 'Algorithm', 'als');
0 comentarios
Respuestas (0)
Ver también
Categorías
Más información sobre Dimensionality Reduction and Feature Extraction en Help Center y File Exchange.
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!