Question

8.12 The data tuples of Figure 8.25 are sorted by decreasing probability value, as returned by a classifier. For each tuple, compute the values for the number of true positives (TP), false positives (FP). true negatives (TN), and false negatives (FN). Compute the true positive rate (TPR) and false positive rate (FPR). Plot the ROC curve for the data. Tuple # Class | Probability 0.95 3 P 0.78 P 0.66 N 0,60 6 P N 0.52 9N 0,51 0.40 10 

Figure 8.25 Tuples sorted by decreasing score, where the score is the value returned by a probabilistic classifier.

Answer 1

A true positive is an outcome where the model correctly predicts the positive class.

0.95+0.78+0.66+0.55+0.40=3.34

True positive rate is 0.668

A true negative is an outcome where the model correctly predicts the negative class.

0.85+0.60+0.53+0.52+0.51=3.01

True Negative rate is 0.602

A false positive is an outcome where the model incorrectly predicts the positive class.

0.05+0.22+0.34+0.45+0.60=1.66

False Positive rate is 0.332

A false negative is an outcome where the model incorrectly predicts the negative class.

0.15+0.40+0.47+0.48+0.49=1.99

False negative rate is 0.398

Answer 2

Add your answer here!

Answer 3