Comments (3)
Hi, the classes_
attribute is not reserved in deep forest. To solve your problem, one possible solution is to train a random forest classifier on your dataset, and then ingest its classes_
attribute into the deep forest before calling plot_roc_curve
, i.e., model.classes_ = rf.classes_
.
from deep-forest.
Amazing @xuyxu ! Thanks for the advice. It's implement ✅
Nevertheless, may I ask why you have not allocated classes_ for the final model? It is odd that, for instance, the AUROC curve is no longer showable. There might be technical reasons for that.
I am closing the issue anyway 🚀
from deep-forest.
For improving the memory efficiency and inference speed, RandomForestClassifer in deep forest is implemented using arguablely the most compact data structure: four numpy arraies representing splitting feature, threshold, child node index, and prediction from leaf nodes, separately. Therefore, there is no room for another attribute classes_
.
from deep-forest.
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