In supervised learning, class labels of the training samples are

In supervised learning, class labels of the training samples are "known."

The correct answer is "known."The other options for the question were "unknown," "partially known," and  "doesn't matter."It cannot be "unknown," because training samples must be known.It cannot be "partially known," because part of supervised learning is that training samples are known, not in percentages.It cannot be "doesn't matter," because that is never the case when talking about supervised learning. When referring to supervised learning, it includes the notion that class labels of the training samples are "known."Here we are talking about artificial intelligence.Modern technology has allowed the development of machine learning.

We conclude that class labels of the training samples are known in supervised learning. Algorithms need to analyze the information to get correct predictions.

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Supervised learning refers to a machine learning concept whereby the data has a labels upon which the training data learns. Hence, the class labels are known.

Class labels refers to the predictions which we expect the machine learning algorithm to learn from and then make accurate predictions on the test data. Supervised and unsupervised learning differs in that class labels are known in supervised learning while the data isn't labeled in unsupervised learning.

Therefore, the class labels in supervised learning are known.

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