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License: MIT License
Dirichlet MLE python library
License: MIT License
Hi Eric,
Thanks a lot for your Dirichlet fitting code. I am using your code on sparse (i.e. lots of zeros) Bag of Words data from images. When I try dirichlet fitting on those, the fitting process blows up and gives lots of NaNs. Sorry, I am little bit new to Dirichlet models, so if question is preliminary, pointing merely to a reference would be good as well. I tried the same features with Tom Minka's matlab toolbox, and it seems to blow up as well.
Thanks again for your code.
Sincerely,
Abhijit Bendale
PhD Student, University of Colorado
I've used an application of this Dirichlet package by user xuod for the analysis of Morris watermaze data, which is a type of constant sum probability data. Briefly, the data comes from mice swimming in a circular waterfilled pool having four quadrants superimposed on it. The time in each quadrant is recorded over 1 minute, and the dirichlet test is used to determine if the time spent is uniform between all quadrants, or if it non-uniform, suggesting a bias for a particular quadrant. The mice are trained to locate an escape platform hidden in the "target quadrant" which is a test of their memory. It sometimes happens that the data may contain values that are zero when a mouse spends no time at all in one of the quadrants, and the dirichlet.test_uniform() python function fails to converge the model when zeros are present in the data.
Is there any work-around or good solution to address this issue? Can the dataset be transformed in some way to eliminate the zeros without fundamentally altering the data? It seems that adding a constant value to every data point, which gets around the problem of taking the log of zero, would change the data inappropriately.
Thanks for any feedback.
Hi, I notice that in the readme, you suggest install by
pip install git+https://github.com/ericsuh/dirichlet.git
but there is also a https://pypi.python.org/pypi/dirichlet
Why not update the pypi one?
Hi,
can explain to me how can calculate prior distribution by Dirichlet distribution
Hi!
Thanks alot for the package ! I was wondering if there was way to get the concentration parameter a0.
The mle package gives me the vector of proportions a_K/a0. I am interested in getting a_K or a0. Is there a way I can get that from the MLE method
Thanks
Ashish
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