What is the primary purpose of a ROC-AUC (Receiver Operating Characteristic - Area Under the Curve) score in model evaluation?
A. To compare different machine learning algorithms
B. To visualize the model's decision boundary
C. To measure the model's prediction accuracy
D. To evaluate the model's performance on imbalanced datasets
Answer: Option D
Related Questions on Model Evaluation and Validation
What is the primary purpose of a validation dataset in machine learning?
A. To train the model
B. To evaluate the model on unseen data
C. To test the model's performance on training data
D. To visualize data relationships
A. Accuracy
B. Precision
C. Recall
D. F1 Score
A. It reduces the risk of overfitting
B. It reduces the number of folds used in training
C. It increases the model's complexity
D. It decreases the training time
A. Leave-One-Out Cross-Validation (LOOCV)
B. Stratified Sampling
C. Holdout Validation
D. Feature Scaling

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