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MMLU-Pro / 2375 / What is cross-validation and why is it important?

Problem

Answer published by the source. Consult the official source to check your work against its answer.

question

What is cross-validation and why is it important?

category

psychology

options

  1. Cross-validation is only used for validating models in large datasets and is not suitable for small datasets
  2. Cross-validation is a method for enhancing the complexity of a model to improve its performance on a single data set
  3. Cross-validation is not important in small samples
  4. Cross-validation is a method to independently determine the validity of a test on additional samples, it is necessary especially when the initial validation sample is small, to avoid errors and chance factors.
  5. Cross-validation involves using different tests to measure the same variable to ensure the tests agree with each other
  6. Cross-validation is a process where the performance of a test is only assessed once to ensure speed and efficiency
  7. Cross-validation is a method to validate a test without additional samples
  8. Cross-validation is a technique to assess the performance of a model by splitting the data into two sets: one for training and one for final testing
  9. Cross-validation is the replication of a test using the same dataset to confirm the initial results
  10. Cross-validation is a method to determine the validity of a test on the same sample

src

stemez-Psychology

Discussion

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Source and history

upstream_id / Original problem ID
2375
task_id
16522d47-fc18-5586-88d5-753e897bb65e
task_key
default--test--2375
task_revision_id
1
config / split
default / test

Official source

initial import