Version 0.14.0

New Features

• Added a scatterplotmatrix function to the plotting module. (#437)
• Added sample_weight option to StackingRegressor, StackingClassifier, StackingCVRegressor, StackingCVClassifier, EnsembleVoteClassifier. (#438)
• Added a RandomHoldoutSplit class to perform a random train/valid split without rotation in SequentialFeatureSelector, scikit-learn GridSearchCV etc. (#442)
• Added a PredefinedHoldoutSplit class to perform a train/valid split, based on user-specified indices, without rotation in SequentialFeatureSelector, scikit-learn GridSearchCV etc. (#443)
• Created a new mlxtend.image submodule for working on image processing-related tasks. (#457)
• Added a new convenience function extract_face_landmarks based on dlib to mlxtend.image. (#458)
• Added a method='oob' option to the mlxtend.evaluate.bootstrap_point632_score method to compute the classic out-of-bag bootstrap estimate (#459)
• Added a method='.632+' option to the mlxtend.evaluate.bootstrap_point632_score method to compute the .632+ bootstrap estimate that addresses the optimism bias of the .632 bootstrap (#459)
• Added a new mlxtend.evaluate.ftest function to perform an F-test for comparing the accuracies of two or more classification models. (#460)
• Added a new mlxtend.evaluate.combined_ftest_5x2cv function to perform an combined 5x2cv F-Test for comparing the performance of two models. (#461)
• Added a new mlxtend.evaluate.difference_proportions test for comparing two proportions (e.g., classifier accuracies) (#462)

Changes

• Addressed deprecations warnings in NumPy 0.15. (#425)
• Because of complications in PR (#459), Python 2.7 was now dropped; since official support for Python 2.7 by the Python Software Foundation is ending in approx. 12 months anyways, this re-focussing will hopefully free up some developer time with regard to not having to worry about backward compatibility

Bug Fixes

• Fixed an issue with a missing import in mlxtend.plotting.plot_confusion_matrix. (#428)