The Math Behind: Everything about Principle Component Analysis (PCA)

4 min read

PCA reduces the dimensionality of data points that are in many spaces. Some ready codes and libraries allow coders to create PCA easily, however, do you know what is PCA and how does it work mathematically? “The main idea of principal component analysis (PCA) is to reduce the dimensionality of a data set consisting of many variables correlated with each other, either heavily or lightly, while retaining the variation present in the dataset, up to the maximum extent.” Intuitively, Principal Component Analysis allows us to see the position of data points with a lower-dimensional picture. It can be called a projection…...

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Sera Giz Ozel It is Sera, writes and talks about Data Science related topics..