Don't forget to create account on our site to get access to more material made only for free registered user.  

Don't forget to create account on our site to get access to more material made only for free registered user.  

 Get 300+ Questions and answer for Databricks Spark , Machine Learning and Data Science Certifications

Q 27. 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 estimation provides estimates for the model's parameters and the normalizing constant usually ignored in MLEs because ___________

 1. The normalizing constant is always very close to 1

 2. The normalizing constant only has a small impact on the maximum likelihood

 3.  The normalizing constant is often zero and can cause division by zero

4.  Get 300+ Questions and answer for Databricks Spark , Machine Learning and Data Science Certifications

Ans: 4

Exp: (Change the explanation even it is correct)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.

 

 Get 300+ Questions and answer for Databricks Spark , Machine Learning and Data Science Certifications

You have no rights to post comments

Don't forget to create account on our site to get access to more material made only for free registered user.