APPLICATION OF SUPERVISED LEARNING
UNSUPERVISED LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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True
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False
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Either A or B
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None of the above
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Detailed explanation-1: -The first visible difference between K-Means and Gaussian Mixtures is the shape the decision boundaries. GMs are somewhat more flexible and with a covariance matrix ∑ we can make the boundaries elliptical, as opposed to circular boundaries with K-means. Another thing is that GMs is a probabilistic algorithm.
Detailed explanation-2: -Of the clustering algorithms covered in class, Gaussian Mixture Models used for clustering always outperforms k-means and single link clustering. F. Even in practice, the structure in underlying data dictates which algorithm is better for your problem.
Detailed explanation-3: -k-means only considers the mean to update the centroid while GMM takes into account the mean as well as the variance of the data!