APPLICATION OF SUPERVISED LEARNING
UNSUPERVISED LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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yes
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no
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can’t say
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None of the above
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Detailed explanation-1: -Q7. Is it possible that the assignment of observations to clusters does not change between successive iterations in K-Means? When the K-Means machine learning model has reached the local or global minima, it will not alter the assignment of data points to clusters for two successive iterations.
Detailed explanation-2: -K-means clustering does involve a random selection process for the initial centroid guesses, so you may get different results from different runs.
Detailed explanation-3: -Answer:As k-means is an iterative algorithm, it guarantees that it will always converge to the global optimum. Explanation: This one is NOT TRUE about k-means clustering-As k-means is an iterative algorithm, it guarantees that it will always converge to the global optimum.
Detailed explanation-4: -As K increases, the number of centroids increases, and the distance between each data point and its assigned centroid decreases. As a result, the sum of squared distances between the data points and their respective centroids decreases, reducing the error.