DOC update documentation

Author: mfeurer

autosklearn/__version__.py

@@ -1,4 +1,4 @@
 """Version information."""
 
 # The following line *must* be the last in the module, exactly as formatted:
-__version__ = "0.2.1"
+__version__ = "0.3.0"

doc/index.rst

@@ -1,6 +1,6 @@
-*********************
-What is auto-sklearn?
-*********************
+************
+auto-sklearn
+************
 
 .. role:: bash(code)
     :language: bash
@@ -19,8 +19,8 @@ replacement for a scikit-learn estimator:
 *auto-sklearn* frees a machine learning user from algorithm selection and
 hyperparameter tuning. It leverages recent advantages in *Bayesian
 optimization*, *meta-learning* and *ensemble construction*. Learn more about
-the technology behind *auto-sklearn* by reading this paper published at
-the `NIPS 2015 <http://papers.nips.cc/paper/5872-efficient-and-robust-automated-machine-learning.pdf>`_
+the technology behind *auto-sklearn* by reading our paper published at
+`NIPS 2015 <http://papers.nips.cc/paper/5872-efficient-and-robust-automated-machine-learning.pdf>`_
 .
 
 Example
@@ -39,7 +39,7 @@ Example
     >>> print("Accuracy score", sklearn.metrics.accuracy_score(y_test, y_hat))
 
 
-This will run for one hour should result in an accuracy above 0.98.
+This will run for one hour and should result in an accuracy above 0.98.
 
 
 Manual
@@ -59,8 +59,8 @@ namely the 3-clause BSD license.
 Citing auto-sklearn
 *******************
 
-If you use auto-sklearn in a scientific publication, we would appreciate
-references to the following paper:
+If you use auto-sklearn in a scientific publication, we would appreciate a
+reference to the following paper:
 
 
  `Efficient and Robust Automated Machine Learning

doc/installation.rst

@@ -12,7 +12,7 @@ System requirements
 auto-sklearn has the following system requirements:
 
 * Linux operating system (for example Ubuntu),
-* Python (>=3.4).
+* Python (>=3.5).
 * C++ compiler (with C++11 supports) and SWIG (version 3.0 or later) 
 
 For an explanation of missing Microsoft Windows and MAC OSX support please
@@ -63,7 +63,7 @@ be solved by installing the *gcc* compiler shipped with AnaConda (as well as
 
 .. code:: bash
 
-    conda install gcc swig
+    conda install gxx_linux-64 gcc_linux-64 swig
 
 
 Windows/OSX compability
@@ -86,7 +86,7 @@ Possible solutions (not tested):
 Mac OSX
 ~~~~~~~
 
-Auto-sklearn is known to work on OSX systems. Nevertheless, there are two
+We currently do not know if *auto-sklearn* works on OSX. There are at least two
 issues holding us back from actively supporting OSX:
 
 * The ``resource`` module cannot enforce a memory limit on a Python process

doc/releases.rst

@@ -11,11 +11,26 @@
 Releases
 ========
 
-Version 0.2.2
+Version 0.3.0
 =============
 
+* Upgrade to scikit-learn 0.19.1.
 * Do not use the ``DummyClassifier`` or ``DummyRegressor`` as part of an
   ensemble. Fixes `#140 <https://github.com/automl/auto-sklearn/issues/140>`_.
+* Fixes #295 by loading the data in the subprocess instead of the main process.
+* Fixes #326: refitting could result in a type error. This is now fixed by
+  better type checking in the classification components.
+* Updated search space for ``RandomForestClassifier``, ``ExtraTreesClassifier``
+  and ``GradientBoostingClassifier`` (fixes #358).
+* Removal of constant features is now a part of the pipeline.
+* Allow passing an SMBO object into the ``AutoSklearnClassifier`` and
+  ``AutoSklearnRegressor``.
+
+Contributors
+~~~~~~~~~~~~
+
+* Matthias Feurer
+* Jesper van Engelen
 
 Version 0.2.1
 =============

requirements.txt

@@ -18,5 +18,5 @@ pandas
 
 ConfigSpace>=0.4.0,<0.5
 pynisher>=0.4
-pyrfr>=0.6.1,<0.8
+pyrfr>=0.7,<0.8
 smac