PCA VS ICA (Contrasts)
PCA reduces data set variables while keeping information.
PCA reduces data set variables while keeping information.
ICA splits a mixed signal into independent components.
ICA splits a mixed signal into independent components.
ICA finds independent data sub-elements
ICA finds independent data sub-elements
PCA gets you a reduced-rank representation.
PCA gets you a reduced-rank representation.
ICA reduces a large data collection into self-organized components.
ICA reduces a large data collection into self-organized components.
PCA is used for image compression, facial recognition, and computer vision.
PCA is used for image compression, facial recognition, and computer vision.
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