COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Yes, It is supervised
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No, it is unsupervised.
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Either A or B
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None of the above
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Detailed explanation-1: -K-Means clustering is an unsupervised learning algorithm. There is no labeled data for this clustering, unlike in supervised learning.
Detailed explanation-2: -K-Means unsupervised classification calculates initial class means evenly distributed in the data space then iteratively clusters the pixels into the nearest class using a minimum distance technique. Each iteration recalculates class means and reclassifies pixels with respect to the new means.
Detailed explanation-3: -K-Means Clustering is an Unsupervised Learning algorithm, which groups the unlabeled dataset into different clusters.
Detailed explanation-4: -IBM. What is the k-nearest neighbors algorithm? The k-nearest neighbors algorithm, also known as KNN or k-NN, is a non-parametric, supervised learning classifier, which uses proximity to make classifications or predictions about the grouping of an individual data point.
Detailed explanation-5: -“K-means clustering is a method of vector quantization, originally from signal processing, that aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean, serving as a prototype of the cluster.” –