If you are using guassian mixture models with the expectation-maximization framework for clustering a set of data points into two clusters, which of the following assumptions are important: Selection applicable: A. All the data points are labeled B. All the data points are generated from exactly two gaussian distributions C. All the data points are generated from one gaussian distribution D. All the data points follow n 'gaussian distributions' where n >2.

Q: What is the likelihood ratio p(x|C₁) p(x|C₂) in the case of Gaussian densities?

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A: The given question comes under multiple choice selected based question.

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A: Answer: I have given answered in the handwritten format in brief explanation.

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A: The question has been answered in step2

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Q: What is the likelihood ratio p(x|C₁) p(x|C₂) in the case of Gaussian densities?

A: Likelihood Ratio - The likelihood that a specific test result would be anticipated in a patient with…

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A: Given question are true or false question so we provide both true and false explanation.

Q: Consider the same house rent prediction problem where you are supposed to predict price of a house…

A: The solution to the above question is:

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A: ANSWER:

Q: What is an example of a data set with a non-Gaussian distribution.

A:

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A: Let's see the solution

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A: The question has been answered in step2

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A: The divergence between two distributions of the same random variable is found using KL divergence.