MLS-C01 Question #301: Real Exam Question with Answer & Explanation

Question

A medical device company is building a machine learning (ML) model to predict the likelihood of device recall based on customer data that the company collects from a plain text survey. One of the survey questions asks which medications the customer is taking. The data for this field contains the names of medications that customers enter manually. Customers misspell some of the medication names. The column that contains the medication name data gives a categorical feature with high cardinality but redundancy. What is the MOST effective way to encode this categorical feature into a numeric feature?

Options

• ASpell check the column. Use Amazon SageMaker one-hot encoding on the column to transform a
• BFix the spelling in the column by using char-RNN. Use Amazon SageMaker Data Wrangler one-
• CUse Amazon SageMaker Data Wrangler similarity encoding on the column to create embeddings
• DUse Amazon SageMaker Data Wrangler ordinal encoding on the column to encode categories