SAutomata
Inference and Learning in Stochastic Automata
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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.0 |
rolling linux/jammy R-4.5 | SAutomata_0.1.0.tar.gz |
37.6 KiB |
0.1.0 |
rolling linux/noble R-4.5 | SAutomata_0.1.0.tar.gz |
37.5 KiB |
0.1.0 |
rolling source/ R- | SAutomata_0.1.0.tar.gz |
6.3 KiB |
0.1.0 |
latest linux/jammy R-4.5 | SAutomata_0.1.0.tar.gz |
37.6 KiB |
0.1.0 |
latest linux/noble R-4.5 | SAutomata_0.1.0.tar.gz |
37.5 KiB |
0.1.0 |
latest source/ R- | SAutomata_0.1.0.tar.gz |
6.3 KiB |
0.1.0 |
2026-04-26 source/ R- | SAutomata_0.1.0.tar.gz |
6.3 KiB |
0.1.0 |
2026-04-23 source/ R- | SAutomata_0.1.0.tar.gz |
6.3 KiB |
0.1.0 |
2026-04-09 windows/windows R-4.5 | SAutomata_0.1.0.zip |
40.2 KiB |
0.1.0 |
2025-04-20 source/ R- | SAutomata_0.1.0.tar.gz |
6.3 KiB |