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Problem

1. What is cross-validation? How might we pick the right value of k for k-fold cross validation?

2. How might we know whether we have collected enough data to train a model?

3. Explain why we have training, test, and validation data sets and how they are used effectively?

4. Suppose we want to train a binary classifier where one class is very rare. Give an example of such a problem. How should we train this model? What metrics should we use to measure performance?

 

Computer Engineering, Engineering

  • Category:- Computer Engineering
  • Reference No.:- M92783049

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