COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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50cm
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Very large
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Size of a brick
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Tiny
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Detailed explanation-1: -Hierarchical clustering, also known as hierarchical cluster analysis (HCA), is an unsupervised clustering algorithm that can be categorized in two ways; they can be agglomerative or divisive.
Detailed explanation-2: -The Latent Dirichlet Allocation (LDA) model and Gaussian mixture models are also commonly used in clustering. In addition to clustering, unsupervised learning may be used to determine how data is distributed in space (density estimation).
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: -Twin sample validation can be used to validate results of unsupervised learning. It should be used in combination with internal validation. It can prove to be highly useful in case of time-series data where we want to ensure that our results remain same across time.