scores

initsa

<p>Optional(Conditional Prababilities).</p>

theta

<p>This function is not for end user.</p>

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>.

Muhammad Kashif Hanif

SAutomata

Inference and Learning in Stochastic Automata

Muhammad Umer Sarwar

Rehman Ahmad

Zeeshan Ahmad

Karl-Heinz Zimmermann

scores function

Calculation of Probabilities (Not For End User) — scores

Calculation of Probabilities (Not For End User)

scores: Calculation of Probabilities (Not For End User)

Description

Usage

Arguments

Examples