Apparatus for generating a statistical sequence model called class bi-multigram model with bigram dependencies assumed between adjacent sequences

作者: Yoshinori Sagisaka , Hideharu Nakajima , Sabine Deligne

DOI:

关键词: SequenceVariable lengthProbability distributionClass (philosophy)String (computer science)AlgorithmArtificial intelligenceMathematicsBigramExpectation–maximization algorithmPattern recognitionSequence model

摘要: An apparatus generates a statistical class sequence model called A bi-multigram from input training strings of discrete-valued units, where bigram dependencies are assumed between adjacent variable length sequences maximum N and labels assigned to the sequences. The number times all units occur counted, as well pairs co-occur in strings. initial probability distribution is computed two co-occur, divided by first occurs string. Then, classified into pre-specified desired classes. Further, an estimate calculated using EM algorithm maximize likelihood string with distributions. above processes then iteratively performed generate model.

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