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SciKit-Learn Laboratory (SKLL) makes it easy to run machine learning experiments.

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doc
README.md
classifier.py
example.cfg
generate_predictions.py
run_experiment.py
test_sklearn_wrapper.py

README.md

sklearn wrapper

This project consists of two utilities to make running common sklearn experiments on pre-generated features much simpler.

classifier.py contains a Classifier class and load_examples function that have a simple well-documented API for training, testing, cross-validation, and running grid search on a variety of sklearn models (for details see the documentation).

run_experiment.py is a command-line utility for running a series of classifiers on datasets specified in a configuration file. For more information about the configuration file format, see the example configuration file example.cfg.

Requirements

  • pythongrid must be in your PYTHONPATH
  • export DRMAA_LIBRARY_PATH=/local/research/linux/sge6_2u6/lib/lx24-amd64/libdrmaa.so must be present in your .bashrc
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