Explain MARKOV CHAIN: An algorithm for working with a series of events (for example, a system being in particular states) to predict the possibility of a certain event based on which other events have happened. The identification of probabilistic relationships between the different events means that Markov Chains and Bayesian networks often come up in the same discussions. See also Bayesian network, Monte Carlo method.
Different definitions in web development like Markov Chain in Dictionary M.
- Manual Mean Absolute Error:
- Meaning Also, MAE. The average error of all predicted values when compared with observed values. See also Mean Squared Error, Root Mean Squared Error markov chain.
- Manual Mean Squared Error:
- Meaning average of the squares of all the errors found when comparing predicted values with observed values. Squaring them makes the bigger errors count for more, making Mean Squared Error more popular than markov chain.
- Manual Mean:
- Meaning The average value, although technically that is known as the “arithmetic mean.” (Other means include the geometric and harmonic means.) See also median, mode markov chain.
- Manual Monte Carlo Method:
- Meaning of randomly generated numbers as part of an algorithm. Its use with Markov Chains is so popular that people usually refer to the combination with the acronym MCMC. See also Markov Chain markov chain.
- Manual Mode:
- Meaning occurs most often in a sample of data. Like the median, the mode cannot be directly calculated”[stanton] although it’s easy enough to find with a little scripting. For people who work with statistics markov chain.