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DASCA.SDS.v2025-10-13.q37
Question 30

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Question 30/37

Maximum Likelihood Estimation (MLE) is a way to frame:

A. Large class of problems in Data Science

B. Small class of problems in Data Science

C. Large class of problems in HDFS

D. Small class of problems in HDFS

E. Both A and C

Correct Answer: A

Maximum Likelihood Estimation (MLE) is a statistical method used to estimate the parameters of a model by maximizing the likelihood function - i.e., finding the parameters that make the observed data most probable.
Option A: Correct. MLE provides a framework for a large class of problems in data science, including regression, classification, generative models, and probabilistic inference.
Option B: Incorrect - it applies to many problems, not just a small subset.
Option C & D: Incorrect. HDFS (Hadoop Distributed File System) is a storage technology, unrelated to MLE.
Option E: Incorrect because C is invalid.
Thus, the correct answer is Option A (Large class of problems in Data Science).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Statistical Foundations: Maximum Likelihood Estimation and Inference in Data Science.

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