Amazon MLS-C01 Exam - Topic 2 Question 14 Discussion

Actual exam question for Amazon's MLS-C01 exam

Question #: 14
Topic #: 2

A Data Scientist is developing a machine learning model to predict future patient outcomes based on information collected about each patient and their treatment plans. The model should output a continuous value as its prediction. The data available includes labeled outcomes for a set of 4,000 patients. The study was conducted on a group of individuals over the age of 65 who have a particular disease that is known to worsen with age.

Initial models have performed poorly. While reviewing the underlying data, the Data Scientist notices that, out of 4,000 patient observations, there are 450 where the patient age has been input as 0. The other features for these observations appear normal compared to the rest of the sample population.

How should the Data Scientist correct this issue?

ADrop all records from the dataset where age has been set to 0.

BReplace the age field value for records with a value of 0 with the mean or median value from the dataset.

CDrop the age feature from the dataset and train the model using the rest of the features.

DUse k-means clustering to handle missing features.

Show Suggested Answer

Suggested Answer: A

by Marge at May 03, 2022, 07:02 AM

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5 months ago

This one seems pretty straightforward. I'm pretty confident that low cost is not a challenge with outsourcing, since that's usually one of the main reasons companies choose to outsource in the first place.

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