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Databricks Certified Professional Data Scientist Exam Databricks-Certified-Professional-Data-Scientist Question # 13 Topic 2 Discussion

Databricks Certified Professional Data Scientist Exam Databricks-Certified-Professional-Data-Scientist Question # 13 Topic 2 Discussion

Databricks-Certified-Professional-Data-Scientist Exam Topic 2 Question 13 Discussion:
Question #: 13
Topic #: 2

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


A.

The normalizing constant is always very close to 1


B.

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


C.

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


D.

The normalizing constant doesn't impact the maximizing value


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