1.) The classifier identified 50 mails as spam, only 30 are identified correctly other 90 are not identified. Find Precision, recall and F1-score.
Precision = True Positives / (True Positives + False Positives)
Recall = True Positives / (True Positives + False Negatives)
F1-Score = 2 * (Precision * Recall) / (Precision + Recall)
Given:
True Positives (TP) = 30
False Positives (FP) = 20 (50 total - 30 true)
False Negatives (FN) = 90
Precision = 30 / (30 + 20) = 0.6
Recall = 30 / (30 + 90) = 0.25
F1-Score = 2 * (0.6 * 0.25) / (0.6 + 0.25) = 0.3438
Therefore, the Precision is 0.6, the Recall is 0.25, and the F1-Score is 0.3438.