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Please enable MathJax everywhere it makes sense!
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HMM trainer introduces Hidden Markov Models training in April-ANN :-)
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U de M
deep learnign and its applications (games, player match making)
1. intro to machien learning
2. deep learning paper
3. more recent aper for audo encoders
4. future work
Artifical definition …
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It would be useful when using Monte Carlo techniques to do forecasting if the sample/generate_sequence commands had an option to specify the starting state.
Component: **statistics**
Author: **Wi…
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The attached patch is from Jim Kleckner, not me, so I'm posting it and reviewing it.
Component: **documentation**
Author: **Jim Kleckner**
Reviewer: **William Stein**
Merged: **sage-4.7.1.rc1**
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The generate sequence function for continuous hidden markov models is missing a break statement, which causes the function to incorrectly choose the last state as the starting state for all generate…
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Add more capabilities involving HMM's. This is a continuation of #3726.
Component: **numerical**
_Issue created by migration from https://trac.sagemath.org/ticket/3773_
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I forgot to implement the nsteps and log_likelihood_cuttoff parameters for discrete hidden markov models, despite documenting them as implemented. The attached short patch fixes this oversight.
Co…