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Supervised learning involves training a model using labeled datasets where the algorithm learns to map inputs to the correct output labels. Once trained, the model can predict labels for new, unseen data. It is widely used for classification and regression problems in machine learning. Why Other Options are Wrong: b) Clustering data without labels is unsupervised learning, not supervised learning. c) Continuous learning from feedback describes reinforcement learning. d) Interaction with an environment also refers to reinforcement learning. e) Time series prediction is a specific application of supervised learning but does not define it comprehensively.
24 ? 14 16 39 88.5
...13 182 303 384 433 ?
...60000 2400 120 8 0.8 ?
...2342 2223 2090 1943 1782 ?
...86 36 ? 7 7.5 0.75
7 12 33 ? 635 3804
...219 365 511 ? 803 949
...729 512 343 216 125 ?
...Direction: Which of the following will replace ‘?’ in the given question?
2, ‘?’, 46, 136, 311, 605, 1086
979.001 + 4.0087× 82.79 = ?
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