21. In model evaluation, what is the term for the process of fine-tuning hyperparameters to achieve the best model performance? A. Model Optimization B. Model Training C. Model Evaluation D. Model Selection Answer & Solution Discuss in Board Save for Later Answer & Solution Answer: Option A No explanation is given for this question Let's Discuss on Board
22. Which metric is used to evaluate classification models and represents the ratio of true positives to all actual positive instances? A. Accuracy B. Precision C. Recall D. F1 Score Answer & Solution Discuss in Board Save for Later Answer & Solution Answer: Option C No explanation is given for this question Let's Discuss on Board
23. What is the primary goal of a learning rate schedule in training machine learning models? A. To increase the model's complexity B. To reduce the learning rate over time C. To optimize the loss function D. To reduce the number of training epochs Answer & Solution Discuss in Board Save for Later Answer & Solution Answer: Option B No explanation is given for this question Let's Discuss on Board
24. In model evaluation, what is the term for the process of splitting the dataset into two parts: one for training and one for testing? A. Data Sampling B. Data Cleaning C. Data Splitting D. Data Transformation Answer & Solution Discuss in Board Save for Later Answer & Solution Answer: Option C No explanation is given for this question Let's Discuss on Board
25. Which evaluation metric is often used for imbalanced datasets and represents the harmonic mean of precision and recall? A. Accuracy B. Precision C. Recall D. F1 Score Answer & Solution Discuss in Board Save for Later Answer & Solution Answer: Option D No explanation is given for this question Let's Discuss on Board
26. What is the primary purpose of a learning rate in training machine learning models? A. To increase the model's complexity B. To reduce the model's capacity C. To adjust the size of the training dataset D. To control the step size during gradient descent Answer & Solution Discuss in Board Save for Later Answer & Solution Answer: Option D No explanation is given for this question Let's Discuss on Board
27. In model evaluation, what is the term for the process of comparing different machine learning algorithms to choose the best one? A. Model Optimization B. Model Training C. Model Evaluation D. Model Selection Answer & Solution Discuss in Board Save for Later Answer & Solution Answer: Option D No explanation is given for this question Let's Discuss on Board
28. Which evaluation metric is commonly used for regression models and measures the average absolute difference between predicted and actual values? A. Precision B. Recall C. Mean Absolute Error (MAE) D. F1 Score Answer & Solution Discuss in Board Save for Later Answer & Solution Answer: Option C No explanation is given for this question Let's Discuss on Board
29. What is the primary advantage of using k-fold cross-validation over a single train-test split in model evaluation? A. K-fold cross-validation prevents data leakage B. K-fold cross-validation reduces computational resources C. K-fold cross-validation reduces model complexity D. K-fold cross-validation requires less training data Answer & Solution Discuss in Board Save for Later Answer & Solution Answer: Option A No explanation is given for this question Let's Discuss on Board
30. What is the primary purpose of a confusion matrix 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 performance of a classification model Answer & Solution Discuss in Board Save for Later Answer & Solution Answer: Option D No explanation is given for this question Let's Discuss on Board
