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SAutomata

Inference and Learning in Stochastic Automata

v0.1.0 · Nov 2, 2018 · GPL (>= 3)

Description

Machine learning provides algorithms that can learn from data and make inferences or predictions. Stochastic automata is a class of input/output devices which can model components. This work provides implementation an inference algorithm for stochastic automata which is similar to the Viterbi algorithm. Moreover, we specify a learning algorithm using the expectation-maximization technique and provide a more efficient implementation of the Baum-Welch algorithm for stochastic automata. This work is based on Inference and learning in stochastic automata was by Karl-Heinz Zimmermann(2017) <doi:10.12732/ijpam.v115i3.15>.

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OK 12 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Apr 25, 2026
NOTE 11 OK · 3 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026
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1 tracked
new 0.1.0 Mar 10, 2026

R Observatory began tracking this package on Mar 10, 2026; it first appeared on CRAN Nov 2, 2018. Releases before tracking aren’t shown.