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Q1 Mixture of Gaussian 45 Points Q1.1 8 Points Select all correct about GMM. Q1.2 8 Points Choose all of the following correctly describes the differences between GMM and k-means. Gaussian mixture moel is supervised The number of Gaussian distribution functions used is equal to the number of clusters  Gaussian Mixture model is equivalent to Quadratic Discriminant Analysis of GMM can be decomposed similarly to PCA  Σ k-means often gets stuck in a local minimum, while GMM with EM tends not to GMM is better at capturing clusters of different sizes and orientations  GMM is better at capturing clusters with overlaps  GMM is less prone to overfitting

Q1.3 15 Points Suppose we have a Gaussian mixture of dimensional data with 3 dimensions, and we use a model with full covariance matrices. How many parameters are in the model if we set the number of cluster as 4? 39 Q1.4 7 Points Which of the following contour plots describes a Gaussian distribution with diagonal covariance? Select all that apply.

Q1.5 7 Points The following four clusterings of points into 2 clusters.Appling GMM to which is better than k-means? select all correct A  B C D 

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