active_learning: Active Learning Algorithm Orders candidate intervention...
In robertness/bninfo: Queries and information theoritic operations on Bayesian networks.
Description
Active Learning Algorithm
Orders candidate intervention targets by their expected information gain.
Usage
1
2
Arguments
candidates
candidate intervention targets
beta
dataframe for edge-wise probability prior
debug
if TRUE prints messages useful for debugging.
.data
the historic data used to generate edge probabilities.
algorithm.args
arguments passed to the structure inference algorithm used to calculate edge probabilities.
robertness/bninfo documentation built on May 27, 2019, 10:32 a.m.
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Description
Active Learning Algorithm Orders candidate intervention targets by their expected information gain.
Usage
1 2 |
Arguments
candidates |
candidate intervention targets |
beta |
dataframe for edge-wise probability prior |
debug |
if TRUE prints messages useful for debugging. |
.data |
the historic data used to generate edge probabilities. |
algorithm.args |
arguments passed to the structure inference algorithm used to calculate edge probabilities. |
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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