APPLICATION OF SUPERVISED LEARNING
DEEP LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Which of the following statements justify the Maximum Likelihood approach?
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It returns a model that assigns high probability to observed data
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It minimises the KL divergence KL[p ____ data || p ____ model]
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It minimises the KL divergence KL[p ____ model || p ____ data]
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It minimises the reconstruction error of the data
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Explanation:
Detailed explanation-1: -The KL divergence measures how different two probability distributions are and therefore is natural to measure convergence of the maximum likelihood procedures.
Detailed explanation-2: -Minimizing the K-L divergence is equivalent to minimizing the negative log-likelihood, which is equivalent to maximizing the likelihood between the Poisson model and the data.
Detailed explanation-3: -Which of the following is wrong statement about the maximum likelihood method’s steps? Explanation: The rates of all possible substitutions are chosen so that the base composition remains the same.
There is 1 question to complete.