0.7 release (#206)

docs/sources/CHANGELOG.md

@@ -6,33 +6,33 @@ The CHANGELOG for the current development version is available at
 [https://github.com/rasbt/mlxtend/blob/master/docs/sources/CHANGELOG.md](https://github.com/rasbt/mlxtend/blob/master/docs/sources/CHANGELOG.md).
 
 
-### Version 0.6.1 (TBD)
+### Version 0.7.0 (2017-06-22)
 
 
 
 ##### Downloads
 
-- [Source code (zip)](https://github.com/rasbt/mlxtend/archive/v0.6.1.zip)
-- [Source code (tar.gz)](https://github.com/rasbt/mlxtend/archive/v0.6.1.tar.gz)
+- [Source code (zip)](https://github.com/rasbt/mlxtend/archive/v0.7.0.zip)
+- [Source code (tar.gz)](https://github.com/rasbt/mlxtend/archive/v0.7.0.tar.gz)
 
 ##### New Features
 
-- New [mlxtend.plotting.ecdf](http://rasbt.github.io/mlxtend/user_guide/plotting/ecdf/) function for plotting empirical cumulative distribution functions.
-- New [`StackingCVRegressor`](http://rasbt.github.io/mlxtend/user_guide/plotting/ecdf/) for stacking regressors with out-of-fold predictions to prevent overfitting (via [Eike Dehling](https://github.com/EikeDehling)).
+- New [mlxtend.plotting.ecdf](http://rasbt.github.io/mlxtend/user_guide/plotting/ecdf/) function for plotting empirical cumulative distribution functions ([#196](https://github.com/rasbt/mlxtend/pull/196)).
+- New [`StackingCVRegressor`](http://rasbt.github.io/mlxtend/user_guide/regressor/StackingCVRegressor/) for stacking regressors with out-of-fold predictions to prevent overfitting ([#201](https://github.com/rasbt/mlxtend/pull/201)via [Eike Dehling](https://github.com/EikeDehling)).
 
 ##### Changes
 
 - The TensorFlow estimator have been removed from mlxtend, since TensorFlow has now very convenient ways to build on estimators, which render those implementations obsolete.
-- `plot_decision_regions` now supports plotting decision regions for more than 2 training features. (via [James Bourbeau](https://github.com/jrbourbeau)).
+- `plot_decision_regions` now supports plotting decision regions for more than 2 training features [#189](https://github.com/rasbt/mlxtend/pull/189), via [James Bourbeau](https://github.com/jrbourbeau)).
 - Parallel execution in `mlxtend.feature_selection.SequentialFeatureSelector` and `mlxtend.feature_selection.ExhaustiveFeatureSelector` is now performed over different feature subsets instead of the different cross-validation folds to better utilize machines with multiple processors if the number of features is large ([#193](https://github.com/rasbt/mlxtend/pull/193), via [@whalebot-helmsman](https://github.com/whalebot-helmsman)).
-- Raise meaningful error messages if pandas `DataFrame`s or Python lists of lists are fed into the StackingCVClassifer as a `fit` arguments.
-- The `n_folds` parameter of the `StackingCVClassifier` was changed to `cv` and can now accept any kind of cross validation technique that is available from scikit-learn. For example, `StackingCVClassifier(..., cv=StratifiedKFold(n_splits=3)) or StackingCVClassifier(..., cv=GroupKFold(n_splits=3))` (via [Konstantinos Paliouras](https://github.com/sque)).
+- Raise meaningful error messages if pandas `DataFrame`s or Python lists of lists are fed into the `StackingCVClassifer` as a `fit` arguments ([198](https://github.com/rasbt/mlxtend/pull/198)).
+- The `n_folds` parameter of the `StackingCVClassifier` was changed to `cv` and can now accept any kind of cross validation technique that is available from scikit-learn. For example, `StackingCVClassifier(..., cv=StratifiedKFold(n_splits=3))` or `StackingCVClassifier(..., cv=GroupKFold(n_splits=3))` ([#203](https://github.com/rasbt/mlxtend/pull/203), via [Konstantinos Paliouras](https://github.com/sque)).
 
 ##### Bug Fixes
 
-- `SequentialFeatureSelector` now correctly accepts a `None` argument for the `scoring` parameter to infer the default scoring metric from scikit-learn classifiers and regressors.
-- The `plot_decision_regions` function now supports pre-existing axes objects generated via matplotlib's `plt.subplots`. ([See example](http://rasbt.github.io/mlxtend/user_guide/plotting/plot_decision_regions/#example-6-working-with-existing-axes-objects-using-subplots))
-- Made `math.num_combinations` and `math.num_permutations` numerically stable for large numbers of combinations and permutations
+- `SequentialFeatureSelector` now correctly accepts a `None` argument for the `scoring` parameter to infer the default scoring metric from scikit-learn classifiers and regressors ([#171](https://github.com/rasbt/mlxtend/pull/171)).
+- The `plot_decision_regions` function now supports pre-existing axes objects generated via matplotlib's `plt.subplots`. ([#184](https://github.com/rasbt/mlxtend/pull/184), [see example](http://rasbt.github.io/mlxtend/user_guide/plotting/plot_decision_regions/#example-6-working-with-existing-axes-objects-using-subplots))
+- Made `math.num_combinations` and `math.num_permutations` numerically stable for large numbers of combinations and permutations ([#200](https://github.com/rasbt/mlxtend/pull/200)).
 
 
 ### Version 0.6.0 (2017-03-18)

docs/sources/USER_GUIDE_INDEX.md

@@ -17,6 +17,7 @@
 ## `regressor`
 - [LinearRegression](user_guide/regressor/LinearRegression.md)
 - [StackingRegressor](user_guide/regressor/StackingRegressor.md)
+- [StackingCVRegressor](user_guide/regressor/StackingCVRegressor.md)
 
 ## `feature_selection`
 - [SequentialFeatureSelector](user_guide/feature_selection/SequentialFeatureSelector.md)
@@ -33,9 +34,9 @@
 
 ## `evaluate`
 - [confusion_matrix](user_guide/evaluate/confusion_matrix.md)
-- [lift_score](user_guide/evaluate/lift_score.md)
 - [mcnemar_table](user_guide/evaluate/mcnemar_table.md)
 - [mcnemar](user_guide/evaluate/mcnemar.md)
+- [lift_score](user_guide/evaluate/lift_score.md)
 - [scoring](user_guide/evaluate/scoring.md)
 
 ## `preprocessing`
@@ -71,6 +72,7 @@
 - [enrichment_plot](user_guide/plotting/enrichment_plot.md)
 - [stacked_barplot](user_guide/plotting/stacked_barplot.md)
 - [checkerboard_plot](user_guide/plotting/checkerboard_plot.md)
+- [ecdf](user_guide/plotting/ecdf.md)
 
 ## `math`
 - [num_combinations](user_guide/math/num_combinations.md)
@@ -88,4 +90,4 @@
 - [activation-functions](user_guide/general_concepts/activation-functions.md)
 - [gradient-optimization](user_guide/general_concepts/gradient-optimization.md)
 - [linear-gradient-derivative](user_guide/general_concepts/linear-gradient-derivative.md)
-- [regularization-linear](user_guide/general_concepts/regularization-linear.md)
+- [regularization-linear](user_guide/general_concepts/regularization-linear.md)

mlxtend/__init__.py

@@ -4,4 +4,4 @@
 #
 # License: BSD 3 clause
 
-__version__ = '0.6.1.dev0'
+__version__ = '0.7.0'