Fit Hidden Markov Model

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LLM Evaluation

Evaluated by: xiaomi/mimo-v2-flash:free

Last evaluated: March 29, 2026

Prompt Quality

3.0 /5

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Usefulness

3.0 /5

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Overall Rating

3.0 /5

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---
name: fit-hidden-markov-model
description: >
  Fit hidden Markov models using the Baum-Welch (EM) algorithm with model
  selection, Viterbi decoding for state sequences, and forward-backward
  probabilities. Use when observations are generated by unobservable latent
  states, you need to segment a time series into latent regimes (market
  regimes, speech phonemes, biological sequences), compute sequence
  probabilities, decode the most likely hidden state path, or compare
  models w...

Full prompt length: 14014 characters