Hi all, I was exploring sklearn.semi_supervised.LabelPropagation and I noticed that I get difference results if I train a model and look at "model.transduction_" compared to taking the same model and using "model.predict(X_train)" on the training data.
I couldn't easily find the difference on google, so I began reading through the code but it seems pretty involved and I thought someone here might know the difference off hand. Any help is greatly appreciated :) Thanks, Aidan. _______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
