[Q] In what order do I apply PCA to delineate two categories?

I’m relatively familiar with principal component itself but have a targeted question regarding its application.

Suppose I have 25 rows of data representing 25 successful product lots, characterized by six columns, representing various metrics.

Next I have 5 rows representing failed products lots.

In order to “cluster” or separate the successful from the failed product lots, would I:

(1) apply PCA to the entire data set at once and investigate a score plot

OR

(2) first apply PCA to the 25 successful lots to build a model. then calculate scores using said model for the failed lots and observe where they fall with respect to the old model

submitted by /u/Squanchy187
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Nevin Manimala

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