Summarize advantages and disadvantages of three common methods, including DBSCAN, GMM, and k-means, in case of big data and missing data. In 2D, assume 2 clusters, each randomly generate 10 points, then implement k-means. In 2D, randomly generate 100 points, and free to select the radius and MinPts (key parameters in DBSCAN), identify each point with noise, core, or border in python, then output the density-reachable points. To do GMM estimation, we commonly introduce EM method. please infer the expectation of hidden variable Z in e-step and log-likelihood in m-step.
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