d2l.laurentian.ca_d2l_lms_quizzing_user_quiz_submissions_attempt

Quiz 2 - Results X Attempt 1 of 1 Written Sep 27, 2023 7:33 PM - Sep 27, 2023 7:40 PM Attempt Score 5/5-100 % Overall Grade (Highest Attempt) 5/5-100 % Question 1 1/ 1 point Which of the following are used in a basic linear regression equation? v Height « ~ Y-intercept v ~ Slope v Diameter Question 2 1/ 1 point Which of the following best describes the relationship between ROC (Receiver Operating Characteristic) curve and AUC (Area Under the Curve)? « o AUC s the area under the ROC curve and provides a scalar value representing the classifier's overall ability to distinguish between positive and negative classes. AUC represents the classifier's performance at a specific threshold, while ROC is an overall measure. AUC is the area above the ROC curve and represents the classifier's average performance across all classification thresholds. ROC is a scalar value, while AUC represents the visual depiction of a classifier's performance. Question 3 1/ 1 point Given the following definitions: Precision = TP/(TP+FP) Recall = TP/(TP+FN) If a classifier labels almost all instances as positive, which of the following statements is true? v o Recall will be very high, but precision may be low. Both precision and recall will be very high. Precision will be very high, but recall may be low. Both precision and recall will be very low. Ww Hide question 3 feedback If a classifier labels almost all instances as positive, it means it's classifying both the true positives (TP) and false negatives (FN) from the actual data as positive. Question 4 1/ 1 point In a binary classification confusion matrix, which of the following is NOT a component? False Positives (FP) v o True Division (TD) False Negatives (FN) True Positives (TP) Question 5 1/ 1 point In the context of linear regression, what does the "best-fit line" represent? The line that maximizes the distance from all the data points. The line that passes through every data point in the dataset. The line that ensures all residuals are positive. o The line that minimizes the sum of the squared residuals (or errors) between observed and predicted values.