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Applying ML Techniques to Predict Drawn Japanese Characters. Currently Hiragana is implemented

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Octocat-spinner-32 JPredict
Octocat-spinner-32 JPredictTest
Octocat-spinner-32 JPredict.sln
Octocat-spinner-32 JPredict.suo
Octocat-spinner-32 README.txt
JPredict is a tiny experiement in handwritten input. I wanted to implement a simple classifier to predict Hiragana symbols as they were drawn. 

For building a training set, compile the JPredict project in VS and run it. Feel free to mail me with questions.

The classifier used is a Nearest-Neighbors classifier with stroke-start-point, centroid, and stroke-end-point as the features. The performace is very good with 1 data-item / symbol (so this is a viable approach for 1-shot hiragana recognition).
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