In statistics, maximum-likelihood estimation (MLE) is a method of estimating the parameters of a statistical model. When applied to a data set and given a statistical model, maximum-likelihood…

Question

Options

• AThe normalizing constant is always very close to 1
• BThe normalizing constant only has a small impact on the maximum likelihood
• CThe normalizing constant is often zero and can cause division by zero
• DThe normalizing constant doesn't impact the maximizing value

• A
  5% (1)
• B
  9% (2)
• C
  9% (2)
• D
  77% (17)

Explanation

A normalizing constant is positive, and multiplying or dividing a series of values by a positive number does not affect which of them is the largest. Maximum likelihood estimation is concerned only with finding a maximum value, so normalizing constants can be ignored. Exam Questions, Study Guides, Practice Tests. Lead the way to help you pass any IT Certification exams, 100% Pass Guaranteed or Full Refund. Especially Cisco, Microsoft, CompTIA, Citrix, EMC, HP, Oracle, VMware, Juniper, Check Point, LPI, Nortel, EXIN and so on. Our Slogan: First Test, First Pass. Help you to pass any IT Certification exams at the first try. You can reach us at any of the email addresses listed below. Any problems about IT certification or our products, you could rely upon us, we will give you satisfactory answers in 24 hours.

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