I just wanted to confirm if this was correct :)
For logistic regressions, do the outputs in the training set are actually no different than the outputs that we get as predictions? Is the only reason we have binary outputs as part of the classification for logistic regression is that we know it to be true or not[a student gets admitted or not; the cancer is benign or not].
Technically, could we still have the output as any real value between 0 and 1 in the training set -- e.g., we know %60 that the cancer is benign or %60 that the student will get admitted?
Just to illustrate, let's say we have the outputs as 0's and 1's in a scenario as
34.62365962451697, 78.0246928153624, 0*
*where the first two columns are test scores and the third one is the college admission decision
Would it be okay if we change the 0 to 0.6 and then run logistic regression [assuming the student's chance of admission is 60%]:
34.62365962451697, 78.0246928153624, 0.6
Your answer will be much appreciated!