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Kernel Density Estimation (kde) #1944
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Feel free to write your name below if you are working on this task! This way we avoid wasting manpower on the same algorithm. |
for reference, working on this one. :) |
I am attempting this :) |
@iglesias i figured i needed help on this: |
densities should always be evaluated in log-domain to avoid numerical problems |
I will attempt this as well |
Maybe I'm too late. But I'm also try to impelement it. |
@iglesias @mazumdarparijat this is done, or? |
This is an entrance task for the fundamental machine learning algorithms GSoC project http://www.shogun-toolbox.org/page/Events/gsoc2014_ideas#fundamental.
Scikit-learn has a nice implementation of this algorithm, so feel free to draw inspiration from it: github.com/scikit-learn/scikit-learn/blob/master/sklearn/neighbors/kde.py
This task is fun because the algorithm is not particularly hard to implement and it is possible to make good-looking examples (ask @iglesias if you need an idea for this once the main algorithm and unit test are implemented).
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