COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Finds hidden structures in data
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Learns from data that contains only the inputs
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Learns from data that contains both the inputs and expected outputs
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Learns how an agent should take actions in an environment to maximize a reward function
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Detailed explanation-1: -Explanation: In unsupervised learning, the model learns itself from the data without having a predicted result. Either the data is not given with a target response variable (label), or none chooses to label a response.
Detailed explanation-2: -Machine Learning “Clustering” is the process of grouping similar entities together. The goal of this unsupervised machine learning technique is to find similarities in the data point and group similar data points together.
Detailed explanation-3: -Clustering is an unsupervised learning technique, which groups unlabeled data points based on their similarity and differences. Hence, points are grouped into clusters in such a way that those in a same group have the most similarity with each other, while points in different groups have little to no similarities.
Detailed explanation-4: -Unsupervised learning uses machine learning algorithms to analyze and cluster unlabeled data sets. These algorithms discover hidden patterns in data without the need for human intervention (hence, they are “unsupervised”).