Port over to AutoML common

CONTRIBUTING.md

@@ -30,16 +30,20 @@ Following that we'll tell you about how you can test your changes locally and th
     It's important to work off the latest changes on the **development** branch.
     ```bash
     # With https
-    git clone https://github.com/your-username/auto-sklearn
+    # Note the --recurse-submodules args, we use a submodule autosklearn/automl_common
+    # so it needs to be downloaded too
+    git clone --recurse-submodules https://github.com/your-username/auto-sklearn
 
     # ... or with ssh
-    git clone [email protected]:your-username/auto-sklearn.git
+    git clone --recurse-submodules [email protected]:your-username/auto-sklearn.git
 
     # Navigate into the cloned repo
     cd auto-sklearn
 
     # Create a new branch based off the development one
     git checkout -b my_new_branch development
+
+    git submodule udate --init --recursive  # If you missed the --recurse-submodules arg
 
     # ... Alternatively, if you would prefer a more manual method
     # Show all the available branches with a * beside your current one
@@ -50,6 +54,8 @@ Following that we'll tell you about how you can test your changes locally and th
 
     # Create a new branch based on the currently active branch
     git checkout -b my_new_branch
+
+    git submodule udate --init --recursive  # If you missed the --recurse-submodules arg
     ```
 
     The reason to create a new branch is two fold:
@@ -335,6 +341,9 @@ Lastly, if the feature really is a game changer or you're very proud of it, cons
     cd auto-sklearn
     git checkout -b my_new_branch development
 
+    # Initaize autosklearn/automl_common submodule
+    git submodule update --init --recursive
+
     # Create a virtual environment and activate it so there are no package
     # conflicts
     python -m venv my-virtual-env

MANIFEST.in

@@ -9,6 +9,7 @@ recursive-include autosklearn/experimental *.json
 
 # Remove tests from automl_common
 prune autosklearn/automl_common/test
+exclude autosklearn/automl_common/setup.py
 
 # Include automl_common LICENSE and README
 include autosklearn/automl_common/LICENSE

README.md

@@ -1,4 +1,4 @@
-auto-sklearn
+# auto-sklearn
 
 **auto-sklearn** is an automated machine learning toolkit and a drop-in replacement for a [scikit-learn](https://scikit-learn.org) estimator.
 

scripts/2015_nips_paper/run/score_ensemble.py

@@ -106,6 +106,7 @@ def main(input_directories, output_file, task_id, seed, ensemble_size, n_jobs=1)
         temporary_directory=input_directory,
         output_directory=input_directory + "_output",
         delete_tmp_folder_after_terminate=False,
+        prefix="auto-sklearn"
     )
     valid_labels = backend.load_targets_ensemble()
     score = balanced_accuracy