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Results tagged with pca
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user 311987
Principal component analysis (PCA) is a linear dimensionality reduction technique. It reduces a multivariate dataset to a smaller set of constructed variables preserving as much information (as much variance) as possible. These variables, called principal components, are linear combinations of the input variables.
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How do I analyze clustering post-PCA
All those thoughts were before realizing that I need to run PCA and data normalization. … Here are my questions:
Should I run PCA before the clustering due to risk indicators are high-correlated, or should I first cluster and finally perform PCA to visualize the clusters? …
