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MMLU / For a Gaussian Bayes classifier, which one of these structural assumptions is…

Problem

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question

For a Gaussian Bayes classifier, which one of these structural assumptions is the one that most affects the trade-off between underfitting and overfitting:

choices

  1. Whether we learn the class centers by Maximum Likelihood or Gradient Descent
  2. Whether we assume full class covariance matrices or diagonal class covariance matrices
  3. Whether we have equal class priors or priors estimated from the data
  4. Whether we allow classes to have different mean vectors or we force them to share the same mean vector

subject

machine_learning

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Source and history

task_id
ce50f66f-fc4d-5ee1-b065-b06365abd1f9
task_key
all--test--ce50f66f-fc4d-5ee1-b065-b06365abd1f9
task_revision_id
1
config / split
all / test

Official source

initial import