cnEntropy: Pairwise Node Entropy
In sdnet: Soft-Discretization-Based Bayesian Network Inference
Description
Usage
Arguments
Details
Value
Author(s)
See Also
Description
Calculates the matrix of conditional entropy for each pair of nodes.
Usage
1
2
3
4
cnEntropy(data, pert=NULL)
cnEdgeDistanceKL(data, pert)
cnEdgeDistancePearson(data, pert)
cnEntropyOrder(data, pert=NULL)
Arguments
data
a matrix in row-nodes format or a data.frame in column-nodes format
pert
a binary matrix with the dimensions of data. A value 1 designates the corresponding node in the sample as perturbed.
Details
The conditional entropy of node X with respect to Y is defined as -P(X|Y)logP(X|Y), where P(X|Y) is the sample conditional probability, and this is the value at the (X,Y)'th position in the resulting matrix.
Value
A matrix
Author(s)
N. Balov
See Also
sdnet documentation built on May 2, 2019, 12:43 a.m.
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.
Description Usage Arguments Details Value Author(s) See Also
Description
Calculates the matrix of conditional entropy for each pair of nodes.
Usage
1 2 3 4 | cnEntropy(data, pert=NULL)
cnEdgeDistanceKL(data, pert)
cnEdgeDistancePearson(data, pert)
cnEntropyOrder(data, pert=NULL)
|
Arguments
data |
a |
pert |
a binary |
Details
The conditional entropy of node X with respect to Y is defined as -P(X|Y)logP(X|Y), where P(X|Y) is the sample conditional probability, and this is the value at the (X,Y)'th position in the resulting matrix.
Value
A matrix
Author(s)
N. Balov
See Also
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.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.