A machine learning specialist is developing a regression model to predict rental rates from rental listings. A variable named Wall_Color represents the most prominent exterior wall color of the property. The following is the sample data, excluding all other variables: The specialist chose a model that needs numerical input data. Which feature engineering approaches should the specialist use to allow the regression model to learn from the Wall_Color data? (Choose...

Questions › Category: MLS-C01 › A machine learning specialist is developing a regression model to predict rental rates from rental listings. A variable named Wall_Color represents the most prominent exterior wall color of the property. The following is the sample data, excluding all other variables: The specialist chose a model that needs numerical input data. Which feature engineering approaches should the specialist use to allow the regression model to learn from the Wall_Color data? (Choose…

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A machine learning specialist is developing a regression model to predict rental rates from rental listings. A variable named Wall_Color represents the most prominent exterior wall color of the property. The following is the sample data, excluding all other variables:
 
The specialist chose a model that needs numerical input data.
Which feature engineering approaches should the specialist use to allow the regression model to learn from the Wall_Color data? (Choose two.)

A. Apply integer transformation and set Red = 1, White = 5, and Green = 10.

B. Add new columns that store one-hot representation of colors.

C. Replace the color name string by its length.

D. Create three columns to encode the color in RGB format.

E. Replace each color name by its training set frequency.






 

Suggested Answer: AD

Community Answer: BE




This question is in MLS-C01 AWS Certified Machine Learning – Specialty Exam
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