COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Supervised, unsupervised and reinforcement learning
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Algorithms, decomposition and pseudocode
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Images, labels and rewards
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None of the above
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Detailed explanation-1: -Supervised learning requires a labeled dataset for training. Unsupervised learning identifies hidden data patterns from an unlabeled dataset, while Reinforcement learning does not require data as it learns by interacting with the environment.
Detailed explanation-2: -The three machine learning types are supervised, unsupervised, and reinforcement learning.
Detailed explanation-3: -And, unsupervised learning is where the machine is given training based on unlabeled data without any guidance. Whereas reinforcement learning is when a machine or an agent interacts with its environment, performs actions, and learns by a trial-and-error method.
Detailed explanation-4: -The most commonly used Supervised Learning algorithms are decision tree, logistic regression, linear regression, support vector machine. The most commonly used Unsupervised Learning algorithms are k-means clustering, hierarchical clustering, and apriori algorithm.