What are the possible advantages and disadvantages of using such an approach?

1.       Na¨ıve Bayes is a generative model in which each class corresponds to one mixture component. Design a semi-supervised generalization of the nai¨ıve Bayes model in which each of the k classes contains exactly b > 1 mixture components for a total of b · k mixture components. How would you perform parameter estimation in this model?

2.       The adaptive nearest-neighbor method discussed in the chapter uses a single distortion metric over the entire data space in order to compute the nearest neighbor of a point. Propose a training algorithm to make this metric locally adaptive, so that an optimized distortion metric is used for each test instance based on the local class patterns in the data. What are the possible advantages and disadvantages of using such an approach?

 

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discuss supply and demand along with price elasticity of demand .

I am working on part two of my paper for microeconomics. It is due this evening (11/26/17) by 9:00 MST. The document will need to be about the company of….

Include at least 250 words in your posting and at least 250 words in your reply.  Indicate at least one source or reference in your original post. Please see syllabus for details on submission requirements.

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send a copy of the files over an internet platform to an offsite server.

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