Explain what resampling methods are and why they are useful

Data Science Interview QuestionsCategory: Data ScienceExplain what resampling methods are and why they are useful
MockInterview Staff asked 10 months ago
2 Answers
MockInterview Staff answered 10 months ago
  • repeatedly drawing samples from a training set and refitting a model of interest on each sample in order to obtain additional information about the fitted model
  • example: repeatedly draw different samples from training data, fit a linear regression to each new sample, and then examine the extent to which the resulting fit differ
  • most common are: cross-validation and the bootstrap
  • cross-validation: random sampling with no replacement
  • bootstrap: random sampling with replacement
  • cross-validation: evaluating model performance, model selection (select the appropriate level of flexibility)
  • bootstrap: mostly used to quantify the uncertainty associated with a given estimator or statistical learning method

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agtui answered 10 months ago

Would it be correct to say it allows you to use a data set that has an unbalanced number of true positives and true negatives?

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