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Python wrapper for the Vowpal Wabbit machine learning library.
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A python wrapper for the Vowpal Wabbit machine learning program. More on Vowpal Wabbit at https://github.com/JohnLangford/vowpal_wabbit/wiki Authored by Shilad Sen. Distributed under the Apache Software Foundation License, version 2: http://www.apache.org/licenses/LICENSE-2.0 You can find code examples in test_examples.py. 1. Edit PATH_VW to direct to the executable binary vw 2. Run python ./test_examples.py Common Issues: Works with vw 7.3. Depending on the version, the parameters (like --l2 for l2 regularization) may change change. Requires: - Python >= 2.4 (for the subprocess module and deque). - The vw executable (from the main VW website). Basic usage of the module: - Create VowpalExample objects for both the training and test set. - Create a new Vowpal object and pass the records to the predict method. - Receive predictions as a return value. There are three ways to specify input examples: - A list of VowpalExample objects. The entire dataset must fit in memory. - An ExampleStream object. You can write VowpalExample objects to it, and they do not need to fit in memory. All training examples must appear before testing examples. - A file in the correct input format. All training examples must appear before testing examples. CHANGELOG: - Added methods to support streaming of input examples. TODO: - Support streaming of prediction results so that they don't need to fit in memory.