Principal Component Analysis (PCA) Explained Simply
Автор: numiqo
Загружено: 2026-02-15
Просмотров: 760
Описание:
Principal Component Analysis (PCA) is a method that reduces the number of variables in a dataset by creating new variables (“principal components”) that are combinations of the original ones and capture the most variation in the data—often making the data easier to visualize, compress, or model.
► Principal Component Analysis Calculator
https://numiqo.com/statistics-calcula...
► Example data
https://numiqo.com/statistics-calcula...
► PCA Interactive
https://numiqo.com/lab/pca
► E-BOOK
https://numiqo.com/statistics-book
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