Which is a good choice LDA or PCA for feature reduction in the supervised learning model?
PCA -> Unsupervised Model or use for supervise learning too LDA -> supervise Model Both used for the feature reduction.
Which is batter LDA or PCA for supervising learning feature reduction and why?
Data-set: It is very famous data-set of wine to find out the customer category.
Solution
If you have labels, a supervised approach will usually be much better than an unsupervised approach.
At least if the labels suit your problem.
If you do not have labels, then you can't use LDA.
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