Getting VW working on windows is a real pain. Even though I had the whole environment set up as described on the readme it still took me a good couple of hours to build.
So with absolutely no guarantee or support options here is my built version of vw.exe version 7.7.0. This was built on a Windows 7 x64 box and I have only tested on this one box so use at your own risk!!
If you were after the executable only then there is no need to continue reading, the rest is about python.
So I started playing around with VW.exe and quickly realised that the command line is a terrible place to experiment on a machine learning algorithm. So I started looking for python wrappers and found this. Which is a nice wrapper but it does not work on Windows. So I hacked it up a little (with no permission, sorry Joseph Reisinger) and have a windows friendly version with updated command line options here.
So how do you use the python wrapper?
First we need to convert your data into VW input format I use my pandas extensions helper method: _df_to_vw
You will be able to turn this into a generic converter very easily, infact there are already plenty around such as:
So now you have your files converted, let’s use the classifier:
# where files open file streams to the VW file training_lines = training_vw_file.readlines() testing_lines = testing_vw_file.readlines() VowpalWabbitClassifier().fit(training_lines).\ predict(testing_lines)
The VowpalWabbitClassifier is fully scikit-learn compatible so use it in your cross validations, grid searches, etc with ease. And just have a look at the code to see all the options it supports and if there are missing options please fork and submit back to me.