/opt/conda/lib/python3.7/site-packages/lime/lime_tabular.py in explain_instance(self, data_row, predict_fn, labels, top_labels, num_features, num_samples, distance_metric, model_regressor)
359 if self.mode == "classification":
360 if len(yss.shape) == 1:
--> 361 raise NotImplementedError("LIME does not currently support "
362 "classifier models without probability "
363 "scores. If this conflicts with your "
NotImplementedError: LIME does not currently support classifier models without probability scores. If this conflicts with your use case, please let us know: https://github.com/datascienceinc/lime/issues/16
Logistic Classifier does support probability scores
I'm using Logistic Classifier on a categorical dataset and after I did everything right, I got the following error:
NotImplementedError Traceback (most recent call last) /tmp/ipykernel_33/3771634090.py in
2 k=5
3 exp_lime = explainer.explain_instance(
----> 4 X_test2[i], lr.predict, num_features=k)
/opt/conda/lib/python3.7/site-packages/lime/lime_tabular.py in explain_instance(self, data_row, predict_fn, labels, top_labels, num_features, num_samples, distance_metric, model_regressor) 359 if self.mode == "classification": 360 if len(yss.shape) == 1: --> 361 raise NotImplementedError("LIME does not currently support " 362 "classifier models without probability " 363 "scores. If this conflicts with your "
NotImplementedError: LIME does not currently support classifier models without probability scores. If this conflicts with your use case, please let us know: https://github.com/datascienceinc/lime/issues/16
Logistic Classifier does support probability scores