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innok/sklearn-porter (press backspace or delete to remove)

Porter.py incorrect❗ .... from sklearn.metrics import accuracy_score from sklearn.tree.tree import DecisionTreeClassifier from sklearn.ensemble.weight_boosting import AdaBoostClassifier from sklearn.ensemble.forest ...

there are always the error:ModuleNotFoundError: No module named sklearn_porter

Here are my versions : The scikit-learn 0.21.3 Python 3.7.13 And here is my code. I used the same example as in the notebook. # 1. Load data and train a dummy classifier: X, y = load_iris(return_X_y=True) ...

I m using porter 0.7.4. and scikit-learn 0.20.0 (using conda) and When I used “from sklearn_porter import Porter” I got the error: ImportError: cannot import name Porter Why about it?
question

Thanks
new feature
question

I m using porter 0.7.4. I updated to scikit-learn 0.24.1 (using conda) and got the error: ModuleNotFoundError: No module named sklearn.tree.tree It seems like the imports have changed?? I got it running ...
bug
high priority

1) Is there some way to generate C code which would give me floating point probabilities for every prediction category instead of a binary result? I am using the ExtraTreeModel from sklearn (code ...
enhancement
new feature

# ... porter = Porter(classifier, language= java ) # Compute integrity score: integrity = porter.integrity_score(X) print(integrity) OSError: Windows isn t supported yet
duplicate

Hello, Is there a problem with integrity_score? # Porting porter = Porter(svc_model, language= c ) # Calculate Integrity Score integrity = porter.integrity_score(standardized_features_frame) # Print ...
enhancement
high priority

javac -cp . SVC.java SVC.java:178: error: cannot find symbol SVC clf = new SVC(5, 5, vectors, coefficients, intercepts, weights, linear , scale, 0.0, 3); ...
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ProTip! Restrict your search to the title by using the in:title qualifier.