Package: SAutomata 0.1.0
Muhammad Kashif Hanif
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>.
Authors:
SAutomata_0.1.0.tar.gz
SAutomata_0.1.0.tar.gz(r-4.5-noble)SAutomata_0.1.0.tar.gz(r-4.4-noble)
SAutomata_0.1.0.tgz(r-4.4-emscripten)SAutomata_0.1.0.tgz(r-4.3-emscripten)
SAutomata.pdf |SAutomata.html✨
SAutomata/json (API)
| # Install 'SAutomata' in R: |
| install.packages('SAutomata', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 6 years agofrom:a3a3572abe. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 13 2024 |
| R-4.5-linux | OK | Nov 13 2024 |
Exports:BaumWelchinitSASbackwardscoresSforwardTOC.sampleData
Dependencies:
