What does the term "bias" refer to in model evaluation and validation?
A. The model's flexibility
B. The difference between predicted and actual values
C. The model's ability to generalize to new data
D. The model's ability to fit the training data
Answer: Option B
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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