#soft-clustering

2 questions from Clustering

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mediumAI-checkedClustering

Which statements about Gaussian mixture models (GMMs) used for clustering are true? Select all that apply.

GMMs are more flexible than K-Means but can be more expensive to compute1
In a GMM, every data point gets a probability for each mixture component2
GMMs are sensitive to initialization3
The number of components has no effect on how well a GMM can fit the data4
Like K-Means, a GMM describes a cluster only by its center, so it cannot model elongated clusters5

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