What is the primary advantage of using stratified sampling in model evaluation?
A. It ensures that each class is represented fairly
B. It reduces the risk of overfitting
C. It simplifies the model's architecture
D. It requires less computational resources
Answer: Option A
This Question Belongs to Data Science >> 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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