Databricks Machine Learning Associate Question 164
Select 3You are tasked with building a binary classification model in Databricks to predict whether a customer will churn. After training the model, you evaluate it using the ROC curve and decide to set a threshold for classification at 0.6 instead of the default 0.5. Why is it important to carefully choose this threshold, and what effect does it have on the model's performance?
- A
Setting a higher threshold like 0.6 will decrease the false negative rate.
- B
Lowering the threshold to 0.4 instead of 0.5 would increase the recall of the model.
- C
Changing the threshold affects the trade-off between precision and recall.
- D
The threshold determines the point where the model classifies a prediction as positive or negative.
- E
Threshold changes do not affect the F1 score of the model.
Show answer and explanation
Correct answers: B, C, D
Explanation
The threshold in a classification model determines how predictions are classified as positive or negative. Adjusting the threshold impacts the trade-off between precision and recall, which in turn can affect metrics like F1 score. For example, lowering the threshold increases recall but may decrease precision, while raising the threshold improves precision but may reduce recall. It is crucial to select a threshold based on the use case requirements, such as whether minimizing false negatives or false positives is more critical.
- A. Incorrect.
This is incorrect. Setting a higher threshold (e.g., 0.6) would increase the false negative rate because fewer predictions would be classified as positive.
- B. Correct.
This is correct. Lowering the threshold to 0.4 would classify more predictions as positive, potentially capturing more true positives and improving recall.
- C. Correct.
This is correct. Adjusting the threshold directly impacts the balance between precision (fewer false positives) and recall (fewer false negatives).
- D. Correct.
This is correct. The threshold is the decision boundary for predicting whether a sample belongs to the positive or negative class.
- E. Incorrect.
This is incorrect. Changing the threshold does affect the F1 score, as it impacts precision and recall, which are both components of the F1 score.