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MMLU-Pro / 10668 / Statement 1| When learning an HMM for a fixed set of observations, assume we do…

Problem

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question

Statement 1| When learning an HMM for a fixed set of observations, assume we do not know the true number of hidden states (which is often the case), we can always increase the training data likelihood by permitting more hidden states. Statement 2| Collaborative filtering is often a useful model for modeling users' movie preference.

category

computer science

options

  1. True, True
  2. True, False
  3. False, False
  4. False, True

src

ori_mmlu-machine_learning

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Source and history

upstream_id / Original problem ID
10668
task_id
5555f7f2-7128-5746-bef8-216319e05d5b
task_key
default--test--10668
task_revision_id
1
config / split
default / test

Official source

initial import