著者

東 藍 新保仁 松本 裕治 Azuma Ai Shimbo Masashi Matsumoto Yuji

雑誌

データマイニングと統計数理研究会(第 12 回)

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When we apply machine learning or data mining technique to sequential data, it is often required to take a summation over all the possible sequences. We cannot calculate such a summation directly from its definition in practice. Although the ordinary forward-backward algorithm provides an efficient way to do it, it is applicable to quite limited types of summations. In this paper, we propose general algebraic frameworks for generalization of the forward-backward algorithm. We show some examples falling within this framework and their importance.