APPLICATION OF SUPERVISED LEARNING
UNSUPERVISED LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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A student has applied the k-means algorithm to an unsupervised problem.On analysis they find that the mean distance between data instances and the cluster centres which they are assigned is 0. What does this mean?
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That this position of k centroids is optimal for this dataset
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That the chosen value of k must at least equal the number of datapoints
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None of these
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None of the above
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Explanation:
Detailed explanation-1: -K-Means clustering is an unsupervised learning algorithm. There is no labeled data for this clustering, unlike in supervised learning. K-Means performs the division of objects into clusters that share similarities and are dissimilar to the objects belonging to another cluster.
Detailed explanation-2: -Out of all the options, the K-Means clustering algorithm is most sensitive to outliers as it uses the mean of cluster data points to find the cluster center.
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