rasbt/mlxtend: v0.5.0

Version 0.5.0 Downloads Source code (zip) Source code (tar.gz) New Features New ExhaustiveFeatureSelector estimator in mlxtend.feature_selection for evaluating all feature combinations in a specified range The StackingClassifier has a new parameter average_probas that is set to True by default to maintain the current behavior. A deprecation warning was added though, and it will default to False in future releases (0.6.0); average_probas=False will result in stacking of the level-1 predicted probabilities rather than averaging these. New StackingCVClassifier estimator in 'mlxtend.classifier' for implementing a stacking ensemble that uses cross-validation techniques for training the meta-estimator to avoid overfitting (Reiichiro Nakano) New OnehotTransactions encoder class added to the preprocessing submodule for transforming transaction data into a one-hot encoded array The SequentialFeatureSelector estimator in mlxtend.feature_selection now is safely stoppable mid-process by control+c, and deprecated print_progress in favor of a more tunable verbose parameter (Will McGinnis) New apriori function in association to extract frequent itemsets from transaction data for association rule mining New checkerboard_plot function in plotting to plot checkerboard tables / heat maps New mcnemar_table and mcnemar functions in evaluate to compute 2x2 contingency tables and McNemar's test Changes All plotting functions have been moved to mlxtend.plotting for compatibility reasons with continuous integration services and to make the installation of matplotlib optional for users of mlxtend's core functionality Added a compatibility layer for scikit-learn 0.18 using the new model_selection module while maintaining backwards compatibility to scikit-learn 0.17. Bug Fixes mlxtend.plotting.plot_decision_regions now draws decision regions correctly if more than 4 class labels are present Raise AttributeError in plot_decision_regions when the X_higlight argument is a 1D array (chkoar