Description Usage Arguments Value Note References Examples
View source: R/static_inference.R
Runs MAP inference from an AMIDST data stream
1 2 | map_inference_from_stream(network, map_variables, evidence_variables,
input_stream, sample_size, parallel = T, seed = 3L)
|
network |
a java object of class |
map_variables |
a vector with the name of the variables over which the MAP configuration will be computed |
evidence_variables |
a vector with the names of the observed variables |
input_stream |
and AMIDST data stream |
sample_size |
the sample size to be used for estimating marginals |
parallel |
a |
seed |
the seed for the genertion of random numbers |
a data.frame
with the MAP configuration of the
variables of interest for each item in the stream
The function computes the MAP configuration of the variables of interest given some evidence for all the items in the input stream.
D. Ramos-Lopez, A. Salmeron, R. Rumi, A.M. Martinez, T.D. Nielsen, A.R. Masegosa, H. Langseth, A.L. Madsen (2016) Scalable MAP inference in Bayesian networks based on a Map-Reduce approach. PGM'2016. JMLR: Workshop and Conference Proceedings, vol. 52: 415-425.
1 2 3 4 5 6 7 8 9 10 | ## Not run:
network <- load_amidst_bn(system.file("extdata","WasteIncinerator.bn",
package="ramidst"))
sample_stream <- amidst_data_stream(system.file("extdata",
"WasteIncineratorSample.arff",package="ramidst"))
map_configurations <- map_inference_from_stream(network,c("D","B"),c("W"),
sample_stream,5L)
map_configurations
## End(Not run)
|
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