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thank you for your work at the gplearn package - I really appreciate your work!
I'm quite interested in implementing genetic programming for multiclass classification, however, I'm quite out-of-time and probably won't manage to wait until the release of 0.3 version. I've just wondered, if I could use either One vs. One or One vs. All approach (like in SVM), using binary classification.
What would be the best way to implement binary classifier using estimators, which are available in gplearn so far? I've tried some of my ideas, however, I'm not very skilled in statistics and my attempts ended in failure.
I would be really thankful for giving me a hand.
Best regards,
Mateusz
The text was updated successfully, but these errors were encountered:
Hey Trevor,
thank you for your work at the gplearn package - I really appreciate your work!
I'm quite interested in implementing genetic programming for multiclass classification, however, I'm quite out-of-time and probably won't manage to wait until the release of 0.3 version. I've just wondered, if I could use either One vs. One or One vs. All approach (like in SVM), using binary classification.
What would be the best way to implement binary classifier using estimators, which are available in gplearn so far? I've tried some of my ideas, however, I'm not very skilled in statistics and my attempts ended in failure.
I would be really thankful for giving me a hand.
Best regards,
Mateusz
The text was updated successfully, but these errors were encountered: