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HungaBunga: Brute-Force all sklearn models with all parameters using .fit .predict!

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ExtraTreesClassifier ============================================================ Model accuracy Time/clf (s) --------------------------- ---------- -------------- SGDClassifier -inf inf LogisticRegression -inf inf Perceptron -inf inf PassiveAggressiveClassifier -inf inf MLPClassifier -inf inf KMeans -inf inf KNeighborsClassifier -inf inf...

Hi, I am getting below error while initializing. Please advise the solution FYI - All libraries are updated with latest version --------------------------------------------------------------------------- ModuleNotFoundError Traceback (most recent call last) in ()...

If I want multi-label, for the y vector should I use OHC or a 1-d array?

Hi, I downloaded and put the package in site-packages. When importing, I get the error: ``` from regression import HungaBungaRegressor ModuleNotFoundError: No module named 'regression' ```

Hello This is the code i'm trying to run: ``` X_train, y_train = prepare_data_for_ml(X_train, y_train) y_train, y_test = prepare_data_for_ml(X_test, y_test) clf = HungaBungaClassifier() clf.fit(X_train, y_train) clf.predict(X_test) ``` That's the error:...

Hey! How did you determine the parameter ranges for all the models? And have you thought about the implications of having them specified by name and not by model (i.e....

Please, add gradient boosting libraries, like CatBoost, XGBoost, LightGBM.