mlxtend
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rasbt
A library of extension and helper modules for Python's data analysis and machine learning libraries.
Similar to from mlxtend.frequent_patterns import apriori frequent_itemsets = apriori(df, min_support=0.6, use_colnames=True) we could implement Eclat and FPGrowth as alternatives to apriori for frequent itemset generation. For instance, from mlxtend.frequent_patterns import...
add fixed_features ### Description ### Related issues or pull requests ### Pull Request Checklist - [ ] Added a note about the modification or contribution to the `./docs/sources/CHANGELOG.md` file (if...
Add https://github.com/kaz-Anova/StackNet as a reference for `use_features_in_secondary` for `StackingClassifier` and `StackingCVClassifier`. They point to a Kaggle competition and blog post that might also be worthwhile mentioning.
#### Describe the bug Waiting through a long EFS run, hoping to get some progress feedback, I don't see any progress shown anywhere. #### Steps/Code to Reproduce ```python from sklearn.linear_model...
#### Describe the workflow you want to enable When passing a pandas Dataframe into `SequentialFeatureSelector`, pass the dataframe into the estimator's fit method ([sequential_feature_selector.py#L432](https://github.com/rasbt/mlxtend/blob/master/mlxtend/feature_selection/sequential_feature_selector.py#L432)) - not a numpy array as...
There is an unnecessary warning ``` /Users/sebastian/miniforge3/lib/python3.9/site-packages/mlxtend/classifier/ensemble_vote.py:166: UserWarning: fit_base_estimators=False enforces use_clones to be `False` warnings.warn("fit_base_estimators=False " ``` when both `use_clones` and `fit_base_estimators` are `False`: ``` eclf = EnsembleVoteClassifier(clfs=(clf1, clf2, clf3),...
I think the more modern version of python setup.py develop is pip install -e . The contributor guide should probably be updated with pip install -r requirements.txt pip install -e...
> Just a suggestion: You may want to add to the contributor guide that the contributors should do git add and git commit after correcting the format with black, before...
Based on the discussion in #915 > Probably you mean 3rd party Jupyter Lab extension like nb_black, but in this case I used black feature to format notebooks: https://black.readthedocs.io/en/stable/change_log.html?#id31 Oh...
From the discussion in #915: > In this statement I mean that to check documentation after adding new sections, new contributor should run this command to convert all notebooks to...