I am not sure how to interpret the results of my decision tree after I had used target encoding, could someone clarify? The example below doesn't need target encoding just for explanation of my confusion here.
For instance I am trying to classify if a fruit is rotten or not given its age and fruit type. I use target encoding for the fruit column:
I then get the following decision tree with default sklearn decision tree classifier parameters:
I believe after encoding I have lost information about fruit type and I can only say that if fruit_target <= 0.841 then the fruit is rotten if smaller, else not rotten. But then how do i interpret 0.841; what does it mean?