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README.rst

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~~~~~~~~~~~~~~~~~~~~~~
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The main utility we provide is called ``run_experiment`` and it can be used to
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easily run a series of learners on datasets specified in a configuration file
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easily run a series of learners on datasets specified in a configuration file
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like:
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.. code:: ini
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experiment_name = Titanic_Evaluate_Tuned
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# valid tasks: cross_validate, evaluate, predict, train
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task = evaluate
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[Input]
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# these directories could also be absolute paths
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# these directories could also be absolute paths
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# (and must be if you're not running things in local mode)
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train_directory = train
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test_directory = dev
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label_col = Survived
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# Column in CSV containing instance IDs (if any)
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id_col = PassengerId
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[Tuning]
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# Should we tune parameters of all learners by searching provided parameter grids?
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grid_search = true
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# Function to maximize when performing grid search
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objectives = ['accuracy']
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[Output]
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# again, these can/should be absolute paths
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log = output
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~~~~~~~~~~
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If you just want to avoid writing a lot of boilerplate learning code, you can
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also use our simple Python API. The main way you'll want to use the API is through
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also use our simple Python API which also supports pandas DataFrames.
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The main way you'll want to use the API is through
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the ``Learner`` and ``Reader`` classes. For more details on our API, see
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`the documentation <https://skll.readthedocs.org/en/latest/api.html>`__.
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While our API can be broadly useful, it should be noted that the command-line
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While our API can be broadly useful, it should be noted that the command-line
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utilities are intended as the primary way of using SKLL. The API is just a nice
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side-effect of our developing the utilities.
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.. image:: doc/skll.png
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:alt: SKLL logo
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:align: right
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.. container:: clear
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.. image:: doc/spacer.png
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- `Grid Map <https://warehouse.python.org/project/gridmap>`__ (only required if you plan
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to run things in parallel on a DRMAA-compatible cluster)
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- `joblib <https://warehouse.python.org/project/joblib>`__
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- `PyYAML <https://warehouse.python.org/project/PyYAML>`__
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- `ruamel.yaml <http://yaml.readthedocs.io/en/latest/overview.html>`__
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- `configparser <https://warehouse.python.org/project/configparser>`__ (only required for
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Python 2.7)
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- `logutils <https://warehouse.python.org/project/logutils>`__ (only required for Python 2.7)

conda-recipe/unix/skll/meta.yaml

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package:
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name: skll
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version: 1.2
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version: 1.2.1
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source:
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path: ../../../../skll

conda-recipe/windows/skll/meta.yaml

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package:
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name: skll
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version: 1.2
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version: 1.2.1
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source:
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path: ../../../../skll

skll/version.py

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:organization: ETS
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"""
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__version__ = '1.2'
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__version__ = '1.2.1'
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VERSION = tuple(int(x) for x in __version__.split('.'))

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