Inferring Statistically Significant Hidden Markov Models
Lu Yu; Jason Schwier; Ryan Craven; Richard R. Brooks; Christopher Griffin · 2013 · IEEE Transactions on Knowledge and Data Engineering
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract (excerpt)
Hidden Markov models (HMMs) are used to analyze real-world problems. We consider an approach that constructs minimum entropy HMMs directly from a sequence of observations. If an insufficient amount of observation data is used to generate…
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Metadata source: OpenAlex · DOI 10.1109/tkde.2012.93