Hello everyone,
I would like to ask for those willing to begin reviewing my new
sklearn.kalman module (found here:
https://github.com/scikit-learn/scikit-learn/pull/862 ). It is a module
that implements the Kalman Filter, Kalman Smoother, and EM algorithm for
Linear-Gaussian models with the ability to handle missing observations. As
far as Kalman Filter implementations go, I believe it is already more
complete than any other package I've seen for Linear-Gaussian state
estimation. As it is currently implemented in pure Python/NumPy, there is
significant room for speed improvements, but the core implementation is
correct and readily usable. I have included documentation (
doc/modules/kalman.rst ), examples ( examples/kalman ), a dataset for
testing ( sklearn/datasets/data/kf_vars.mat ), and test cases with 90%
coverage ( sklearn/tests/test_kalman.py ).
Any and all comments are appreciated, and I would really love to see this
module accepted into sklearn. Let me know if there's anything I can do to
make your job easier!
Thanks,
Daniel Duckworth
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