markov process Sentence Examples
- The Markov process models the stochastic progression of a system through a sequence of states.
- Markov processes are widely used to analyze time series data in various fields, such as finance, biology, and social sciences.
- In a Markov process, the future state of the system depends only on the present state, not on the past sequence of states.
- The transition matrix of a Markov process describes the probabilities of moving from one state to another.
- Markov processes can be used to predict future behavior by estimating the probabilities of transitioning between states.
- Time-homogeneous Markov processes have transition probabilities that remain constant over time.
- Hidden Markov models (HMMs) are a specific type of Markov process used in machine learning for various applications, such as speech recognition and text analysis.
- Markov blankets are sets of nodes in a Bayesian network that shield a target node from the influence of all other nodes.
- The Markov chain Monte Carlo (MCMC) algorithm uses Markov processes to generate samples from complex probability distributions.
- Markov processes are powerful tools for modeling and studying random processes that occur in various systems.
markov process Meaning
markov process (n)
a simple stochastic process in which the distribution of future states depends only on the present state and not on how it arrived in the present state
Synonyms & Antonyms of markov process
No Synonyms and anytonyms found
FAQs About the word markov process
a simple stochastic process in which the distribution of future states depends only on the present state and not on how it arrived in the present state
No synonyms found.
No antonyms found.
The Markov process models the stochastic progression of a system through a sequence of states.
Markov processes are widely used to analyze time series data in various fields, such as finance, biology, and social sciences.
In a Markov process, the future state of the system depends only on the present state, not on the past sequence of states.
The transition matrix of a Markov process describes the probabilities of moving from one state to another.
