Applying PCA for Feature Reduction on UCI Bank Data
Principal Component Analysis (PCA) allows us to reduce the dimension of our data while trying to retain most of the information. This method is especially important on datasets with large number of observations and features. Datasets with a large observations and features can get computationally expensive with some models. In…
