APPLICATION OF SUPERVISED LEARNING
NEURAL NETWORK
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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True
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False
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Either A or B
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None of the above
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Detailed explanation-1: -In multitask classification, there are multiple different outcome variables and one label is applied for each outcome variable. In multilabel classification, there is one outcome variable but multiple labels can be applied for that outcome variable.
Detailed explanation-2: -Multi-label classification involves predicting zero or more class labels. Unlike normal classification tasks where class labels are mutually exclusive, multi-label classification requires specialized machine learning algorithms that support predicting multiple mutually non-exclusive classes or “labels.”
Detailed explanation-3: -Single-label Classification is the process of classifying data that only has one class label. Multi-label classification, on the other hand, is the classification task where the data has two or more class labels. Different algorithms have different approaches to classifying multi-label instances.