COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Classifying emails as spam or not spam
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Watching you label emails as spam or not spam
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The number of emails correctly classified as spam/not spam
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None of the above
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Detailed explanation-1: -Question: Suppose your email program watches which emails you do or do not mark as spam, and based on that learns how to better filter spam. What is the task T in this setting? Classifying emails as spam or not spam.
Detailed explanation-2: -Naïve Bayes example code The below example code is to predict whether the person has diabetes or not. In order to predict that we have made use of Gaussian Naïve Bayes algorithm and also to detect the accuracy of our model.
Detailed explanation-3: -Clustering and Association are two types of Unsupervised learning.
Detailed explanation-4: -Unsupervised learning allows us to approach problems with little or no idea what our results should look like. We can derive structure from data where we don’t necessarily know the effect of the variables. We can derive this structure by clustering the data based on relationships among the variables in the data.