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AutoViML / Auto_ViML

Automatically Build Multiple ML Models with a Single Line of Code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
Apache License 2.0
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NameError: name 'EntropyBinningTransformer' is not defined #40

Closed GDGauravDutta closed 4 months ago

GDGauravDutta commented 4 months ago

NameError Traceback (most recent call last) Cell In[5], line 1 ----> 1 m, feats, trainm, testm = Auto_ViML(train, target='FloodProbability',test='', 2 sample_submission='', 3 scoring_parameter='r2', KMeans_Featurizer=False, 4 hyper_param='RS',feature_reduction=True, 5 Boosting_Flag=True, Binning_Flag=True, 6 Add_Poly=3, Stacking_Flag=True,Imbalanced_Flag=False, 7 GPU_flag=True, verbose=2)

File /opt/conda/lib/python3.10/site-packages/autoviml/Auto_ViML.py:1404, in Auto_ViML(train, target, test, sample_submission, hyper_param, feature_reduction, scoring_parameter, Boosting_Flag, KMeans_Featurizer, Add_Poly, Stacking_Flag, Binning_Flag, Imbalanced_Flag, GPU_flag, verbose) 1396 if model_label == 'Single_Label': 1397 ############### BINNING FIRST TIME ################################################## 1398 if Binning_Flag and len(saved_num_vars) > 0: 1399 #### Do binning only when there are numeric features #### 1400 #### When we Bin the first time, we set the entropy_binning flag to False so 1401 #### no numeric variables are removed. But next time, we will remove them later! 1402 # Optionally, select top n variables based on their predictive power 1403 # This step is useful if you want to bin only the most informative variables -> 1404 entropy_binner = EntropyBinningTransformer(replace_vars=False, modeltype=modeltype, top_n_vars=None) 1406 # Fit the transformer to the training data 1407 entropy_binner.fit_transform(X_train, y_train)

NameError: name 'EntropyBinningTransformer' is not defined

AutoViML commented 4 months ago

Hi @GDGauravDutta thanks for testing it out 👍 I have fixed it now. upgrade to latest version and let me know. Auto Vimal

GDGauravDutta commented 4 months ago

https://www.kaggle.com/code/gauravduttakiit/pss4e5-auto-viml?scriptVersionId=177290781 Still the same issue