COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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In a supervised learning model, the algorithm learns on a labeled dataset, providing an answer key that the algorithm can use to evaluate its accuracy on training data. An unsupervised model, in contrast, provides unlabeled data that the algorithm tries to make sense of by extracting features and patterns on its own.
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supervised learning model, the algorithm learns on a labeled dataset, providing an answer key that the algorithm can use to evaluate its accuracy on training data.
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unsupervised model, in contrast, provides unlabeled data that the algorithm tries to make sense of by extracting features and patterns on its own.
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All of Them
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Detailed explanation-1: -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.
Detailed explanation-2: -Supervised learning algorithms are trained using labeled data. Unsupervised learning algorithms are trained using unlabeled data. Supervised learning model takes direct feedback to check if it is predicting correct output or not. Unsupervised learning model does not take any feedback.
Detailed explanation-3: -Supervised and unsupervised learning have one key difference. Supervised learning uses labeled datasets, whereas unsupervised learning uses unlabeled datasets. By “labeled” we mean that the data is already tagged with the right answer. A classification problem uses algorithms to classify data into particular segments.
Detailed explanation-4: -And in Reinforcement Learning, the learning agent works as a reward and action system. Supervised learning maps labelled data to known output. Whereas, Unsupervised Learning explore patterns and predict the output. Reinforcement Learning follows a trial and error method.
Detailed explanation-5: -In a nutshell, supervised learning is when a model learns from a labeled dataset with guidance. And, unsupervised learning is where the machine is given training based on unlabeled data without any guidance.