|Code Listing by Mo Chen|
probability density function of basic distributions
This package contains the functions for computing pdf of following distribution:
6) von Mises-Fisher
7) Kernel density estimator
These functions are intended to be illustration of the content of Chapter 2 of the book Pattern Recognition and Machine Learning by Christopher M. Bishop.
Functions for Information theory, such as entropy, mutual information, KL divergence, etc
This toolbox contains functions for discrete random variables to compute following quantities:
Variational Bayes method (mean field) for GMM can auto determine the number of components
This is the variational Bayesian procedure (also called mean field) for inference of Gaussian mixture model. This is the Bayesian treatment of Gaussian...
Vibterbi algorithm for HMM inference
Viterbi algorithm based on the Python code found at: http://en.wikipedia.org/wiki/Viterbi_algorithm
Also included is an example based on the one from the Wikipedia page.
The code is...
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