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Current tree classification doesn't allow you to use feature vectors that are not constant in length. Nor does the complete ML module. I suggest creating a fixed set of vectors, which can be filled with correct values. Ignoring 0 values for example will never work, since you create a feature dimension that cannot be filled during classification. If you do want the functionality, the only way to do this is to crack open the source code, make adaptations to the algorithm and make a new implementation. If you do so, feel free to submit it as a pull request so that the feature might get added to the library.
