0.2.5
=======

- Added Sequential Backward Selection (mlxtend.sklearn.SBS)
- Added `X_highlight` parameter to `mlxtend.evaluate.plot_decision_regions` for highlighting test data points.
- Added mlxtend.regression.lin_regplot to plot the fitted line from linear regression.
- Added mlxtend.matplotlib.stacked_barplot to conveniently produce stacked barplots using pandas `DataFrame`s.
- Added mlxtend.matplotlib.enrichment_plot

0.2.4
=======

- Added `scoring` to `mlxtend.evaluate.learning_curves` (by user pfsq)
- Fixed setup.py bug caused by the missing README.html file
- matplotlib.category_scatter for pandas DataFrames and Numpy arrays

0.2.3
=======

- Added Logistic regression
- Gradient descent and stochastic gradient descent perceptron was changed
  to Adaline (Adaptive Linear Neuron)
- Perceptron and Adaline for {0, 1} classes
- Added `mlxtend.preprocessing.shuffle_arrays_unison` function to 
  shuffle one or more NumPy arrays.
- Added shuffle and random seed parameter to stochastic gradient descent classifier.
- Added `rstrip` parameter to `mlxtend.file_io.find_filegroups` to allow trimming of base names.
- Added `ignore_substring` parameter to `mlxtend.file_io.find_filegroups` and `find_files`.
- Replaced .rstrip in `mlxtend.file_io.find_filegroups` with more robust regex.
- Gridsearch support for `mlxtend.sklearn.EnsembleClassifier`

0.2.2
=======

- Improved robustness of EnsembleClassifier.
- Extended plot_decision_regions() functionality for plotting 1D decision boundaries.
- Function matplotlib.plot_decision_regions was reorganized  to evaluate.plot_decision_regions .
- evaluate.plot_learning_curves() function added.
- Added Rosenblatt, gradient descent, and stochastic gradient descent perceptrons.

0.2.1
=======

- Added mlxtend.pandas.minmax_scaling - a function to rescale pandas DataFrame columns.
- Slight update to the EnsembleClassifier interface (additional `voting` parameter)
- Fixed EnsembleClassifier to return correct class labels if class labels are not
  integers from 0 to n.
- Added new matplotlib function to plot decision regions of classifiers.

0.2.0
=======

- Improved mlxtend.text.generalize_duplcheck to remove duplicates and prevent endless looping issue.
- Added `recursive` search parameter to mlxtend.file_io.find_files.
- Added `check_ext` parameter mlxtend.file_io.find_files to search based on file extensions.
- Default parameter to ignore invisible files for mlxtend.file_io.find.
- Added `transform` and `fit_transform` to the `EnsembleClassifier`.
- Added mlxtend.file_io.find_filegroups function.

0.1.9
=======

- Implemented scikit-learn EnsembleClassifier (majority voting rule) class.

0.1.8
=======

- Improvements to mlxtend.text.generalize_names to handle certain Dutch last name prefixes (van, van der, de, etc.).
- Added mlxtend.text.generalize_name_duplcheck function to apply mlxtend.text.generalize_names function to a pandas DataFrame without creating duplicates.

0.1.7
=======

- Added text utilities with name generalization function.
- Added  and file_io utilities.

0.1.6
=======

- Added combinations and permutations estimators.

0.1.5
=======

- Added `DenseTransformer` for pipelines and grid search.


0.1.4
=======

- `mean_centering` function is now a Class that creates `MeanCenterer` objects
  that can be used to fit data via the `fit` method, and center data at the column
  means via the `transform` and `fit_transform` method.


0.1.3
=======

- Added `preprocessing` module and `mean_centering` function.


0.1.2
=======

- Added `matplotlib` utilities and `remove_borders` function.


0.1.1
=======

- Simplified code for ColumnSelector.