MLS-C01 · Question #110
A Data Scientist is developing a binary classifier to predict whether a patient has a particular disease on a series of test results. The Data Scientist has data on 400 patients randomly selected…
The correct answer is B. A stratified k-fold cross-validation strategy with k=5. Stratified k-fold cross-validation will enforce the class distribution in each split of the data to match the distribution in the complete training dataset.
Question
A Data Scientist is developing a binary classifier to predict whether a patient has a particular disease on a series of test results. The Data Scientist has data on 400 patients randomly selected from the population. The disease is seen in 3% of the population. Which cross-validation strategy should the Data Scientist adopt?
Options
- AA k-fold cross-validation strategy with k=5
- BA stratified k-fold cross-validation strategy with k=5
- CA k-fold cross-validation strategy with k=5 and 3 repeats
- DAn 80/20 stratified split between training and validation
How the community answered
(40 responses)- A5% (2)
- B73% (29)
- C15% (6)
- D8% (3)
Explanation
Stratified k-fold cross-validation will enforce the class distribution in each split of the data to match the distribution in the complete training dataset.
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