APPLICATION OF SUPERVISED LEARNING
SUPPORT VECTOR MACHINE SVM
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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What is classification
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when the output variable is a category, such as “red” or “blue” or “disease” and “no disease”
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when the output variable is a real value, such as “dollars” or “weight”
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Either A or B
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None of the above
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Explanation:
Detailed explanation-1: -Classification: A classification problem is when the output variable is a category, such as “red” or “blue” or “disease” and “no disease”. Regression: A regression problem is when the output variable is a real value, such as “dollars” or “weight”.
Detailed explanation-2: -Some examples of classification include spam detection, churn prediction, sentiment analysis, dog breed detection and so on.
Detailed explanation-3: -The main difference between supervised and unsupervised learning: Labeled data. The main distinction between the two approaches is the use of labeled datasets. To put it simply, supervised learning uses labeled input and output data, while an unsupervised learning algorithm does not.
There is 1 question to complete.