PCA for feature selection?
DS Q&A #06. Can you describe a scenario where you would use PCA for feature selection in a machine learning model, and another scenario where you would prefer a different technique?
PCA can be a very useful technique for feature selection when you have a large number of highly correlated input features. By performing PCA, you can identify the principal components that account for the most variance in your data. The components that explain only a small fraction of the variance can then be dropped, effectively reducing the dimensiona…
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