APPLICATION OF SUPERVISED LEARNING
CLASSIFICATION IN MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Precision = 33.33%, Recall = 16.66%
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Precision = 25%, Recall = 33.33%
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Precision = 33.33%, Recall
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Precision = 75%, Recall = 33.33%
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Detailed explanation-1: -The spam detection system detects 150 mails as spams, out of which 50 are actually spams. What is the precision and recall of my spam detection system ? A. Precision = 33.33%, Recall = 16.66% B.
Detailed explanation-2: -1 It is estimated that 30% of emails are spam emails. Some software has been applied to filter these spam emails before they reach our inbox. A certain brand of software claims that it can detect 99% of spam emails, and the probability for a false positive (a non-spam email detected as spam) is 5%.
Detailed explanation-3: -One of the first factors email service providers will look at when determining if an email is spam is the IP address of the sender. If a specific IP address has received many complaints in the past, email from that address is more likely to be identified as spam.
Detailed explanation-4: -Machine learning algorithms use statistical models to classify data. In the case of spam detection, a trained machine learning model must be able to determine whether the sequence of words found in an email are closer to those found in spam emails or safe ones.