ramidst (version 0.1.0)

An Interface to the AMIDST Toolbox for Data Stream Processing

Description

Offers a link to some of the functionality of the AMIDST toolbox for handling data streams. More precisely, the package provides inference and concept drift detection using hybrid Bayesian networks.

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Version

Install

install.packages('ramidst')

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Version

0.1.0

License

Apache License 2.0

Maintainer

Antonio Salmeron

Last Published

October 21st, 2016

Functions in ramidst (0.1.0)

dynamic_importance_sampling

Runs belief update from a piece of dynamic evidence over a dynamic Bayesian network

mpe_inference_from_stream

Runs MPE inference from an AMIDST data stream

nb_concept_drift_detector_from_stream

Naive Bayes concept drift detector from an AMIDST data stream

map_inference_from_stream

Runs MAP inference from an AMIDST data stream

save_dynamic_amidst_bn

Saves an AMIDST dynamic BN to a fle

ramidst

ramidst: A package for accessing inference and concept drift detection features provided by the AMIDST Toolbox for handling massive data streams. Visit http://www.amidsttoolbox.com for additional information on the AMIDST Toolbox. This package was partially developed as part of the AMIDST and PGMs-SDA projects. AMIDST has received funding from the European Union's 7th Framework Programme for research, technological development and demonstration under grant no. 619209. PGMs-SDA has received funding from the Spanish Ministry of Economy and Competitiveness and FEDER funds under grant TIN2013-46638-C3-1-P.

print_amidst_bn

Prints an AMIDST model

dbn_generator

Generates a random dynamic Bayesian network

amidst_data_stream

Creates an AMIDST data stream from an arff file

generate_stream_of_sequences

Generates a stream where each item is a full sequence from some dynamic evidence.

load_amidst_bn

Loads an AMIDST BN from a fle

load_dynamic_sequence

Loads an AMIDST dynamic data sequence from a fle