COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Clustering and Association are two types of Unsupervised Learning
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Four types of clustering methods are 1) Exclusive 2) Agglomerative 3) Overlapping 4) Probabilistic
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Unsupervised Learning also known as Self-supervised Learning
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Unsupervised Learning normally applies to gaming
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Detailed explanation-1: -Unsupervised learning is intrinsically more difficult than supervised learning as it does not have corresponding output. The result of the unsupervised learning algorithm might be less accurate as input data is not labeled, and algorithms do not know the exact output in advance.
Detailed explanation-2: -Which of the following is true about unsupervised learning? Unsupervised algorithm only processes “features” and does tags. K-means algorithm and SVM algorithm belong lo unsupervised learning.
Detailed explanation-3: -Self-supervised learning is very similar to unsupervised, except for the fact that self-supervised learning aims to tackle tasks that are traditionally done by supervised learning.
Detailed explanation-4: -Unsupervised learning, also known as unsupervised machine learning, uses machine learning algorithms to analyze and cluster unlabeled datasets. These algorithms discover hidden patterns or data groupings without the need for human intervention.
Detailed explanation-5: -Unsupervised algorithm only processes “features” and does not process tags. Dimensionality reduction algorithm is not unsupervised learning. K-means algorithm and SVM algorithm belong to unsupervised learning. None of the above 2.