aprx_kld: Approximation of the KL-Divergence between two distributions.
In kelvinyangli/mbmml: Learn Markov blankets using Minimum Message Length
Description
This function approximates from the learned distribution to the true distribution.
This is not the full kld, it is the last term in Acid and de Campos (2003)'s paper
on page 37. This function only approximates the kld, because the distributions
are estimated by MLE. The reason to not use the true distribution is to get
fast calculation by approximating the joint distributions from data.
Usage
1
Arguments
data
A categorical dataset.
cptsLearned
The estimated distribution of a learned BN.
logBase
The base of logarithm. Default is 2.
smth
A small value to get rid of 0 occurence.
kelvinyangli/mbmml documentation built on June 29, 2020, 3:12 a.m.
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Description
This function approximates from the learned distribution to the true distribution. This is not the full kld, it is the last term in Acid and de Campos (2003)'s paper on page 37. This function only approximates the kld, because the distributions are estimated by MLE. The reason to not use the true distribution is to get fast calculation by approximating the joint distributions from data.
Usage
1 |
Arguments
data |
A categorical dataset. |
cptsLearned |
The estimated distribution of a learned BN. |
logBase |
The base of logarithm. Default is 2. |
smth |
A small value to get rid of 0 occurence. |
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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