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is chunking by filtering, averaging, or static decision fusion such as
(weighted) voting. Chunking assumes that entries of the series are
independent and can be computed separately; this assumption might
be true for the classification of a global emotional state, but in case of
data, such as actions or user dispositions, the sequential nature has to
be explicitly modeled through recurrent neural networks or hidden
Markov models (see also Chapter 4 in this topic; Bishop, 2006; Glodek
et al., 2011a).
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