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- Inside–outside_algorithm abstract "In computer science, the inside–outside algorithm is a way of re-estimating production probabilities in a probabilistic context-free grammar. It was introduced James K. Baker in 1979 as a generalization of the forward–backward algorithm for parameter estimation on hidden Markov models to stochastic context-free grammars. It is used to compute expectations, for example as part of the expectation–maximization algorithm (an unsupervised learning algorithm).".
- Inside–outside_algorithm wikiPageID "4492939".
- Inside–outside_algorithm wikiPageRevisionID "603043715".
- Inside–outside_algorithm subject Category:Parsing_algorithms.
- Inside–outside_algorithm comment "In computer science, the inside–outside algorithm is a way of re-estimating production probabilities in a probabilistic context-free grammar. It was introduced James K. Baker in 1979 as a generalization of the forward–backward algorithm for parameter estimation on hidden Markov models to stochastic context-free grammars. It is used to compute expectations, for example as part of the expectation–maximization algorithm (an unsupervised learning algorithm).".
- Inside–outside_algorithm label "Inside–outside algorithm".
- Inside–outside_algorithm label "內部外部演算法".
- Inside–outside_algorithm sameAs Inside%E2%80%93outside_algorithm.
- Inside–outside_algorithm sameAs Q6038052.
- Inside–outside_algorithm sameAs Q6038052.
- Inside–outside_algorithm wasDerivedFrom Inside–outside_algorithm?oldid=603043715.