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MMLU-Pro / 10730 / Which among the following prevents overfitting when we perform bagging?

Problem

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question

Which among the following prevents overfitting when we perform bagging?

category

computer science

options

  1. The use of all data without sampling
  2. The practice of validation performed on a random subset of classifiers trained
  3. The use of underfitting to counterbalance overfitting
  4. The use of weak classifiers
  5. The use of classification algorithms which are prone to overfitting
  6. The use of classification algorithms which are not prone to overfitting
  7. The use of sampling with replacement as the sampling technique
  8. The practice of validation performed on every classifier trained
  9. The use of strong classifiers
  10. The use of sampling without replacement as the sampling technique

src

ori_mmlu-machine_learning

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Source and history

upstream_id / Original problem ID
10730
task_id
e4c9b52a-0bf1-57fb-8cbf-4b67a9f51a5b
task_key
default--test--10730
task_revision_id
1
config / split
default / test

Official source

initial import