Deal of The Day! Hurry Up, Grab the Special Discount - Save 25% - Ends In 00:00:00 Coupon code: SAVE25
Welcome to Pass4Success

- Free Preparation Discussions
Mail Us support@pass4success.com
Location US
Mob_nav_barsMENU

Amazon MLS-C01 Exam - Topic 7 Question 63 Discussion

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. and D) Create three columns to encode the color in RGB format.
B) Add new columns that store one-hot representation of colors.
C) Replace the color name string by its length.
E) Replace each color name by its training set frequency.

Amazon MLS-C01 Exam - Topic 7 Question 63 Discussion

Actual exam question for Amazon's MLS-C01 exam
Question #: 63
Topic #: 7
[All MLS-C01 Questions]

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.)

Show Suggested Answer Hide Answer
Suggested Answer: A, D

by Elouise at Sep 18, 2022, 06:19 AM

Limited Time Offer

25%

Off

Get Premium MLS-C01 Questions as Interactive Web-Based Practice Test or PDF

Contribute your Thoughts:

0/2000 characters
Submit Cancel
Dante
7 months ago
Definitely agree with one-hot representation!
upvoted 0 times
...
Sonia
7 months ago
Surprised they didn't mention frequency encoding!
upvoted 0 times
...
Kara
7 months ago
Integer transformation seems arbitrary; not a fan.
upvoted 0 times
...
Kayleigh
8 months ago
I think using RGB columns could be overkill for this.
upvoted 0 times
...
Keneth
8 months ago
One-hot encoding is a solid choice for categorical data!
upvoted 0 times
...
Filiberto
8 months ago
I recall a practice question where frequency encoding was mentioned, so option E might be useful too, but I’m not confident it’s the best approach here.
upvoted 0 times
...
Garry
8 months ago
I think option D, creating RGB columns, could also work, but I wonder if it might be too complex for this model.
upvoted 0 times
...
Providencia
8 months ago
I'm not entirely sure about the integer transformation in option A. It seems a bit arbitrary to assign those specific values to colors.
upvoted 0 times
...
Linsey
8 months ago
I remember we discussed one-hot encoding in class, so I think option B is definitely a good choice for handling categorical data like Wall_Color.
upvoted 0 times
...
Rory
8 months ago
I'm a little confused by the options. Is the checklist or the department-specific plan also a possibility? I want to make sure I understand the question fully before answering.
upvoted 0 times
...
Tommy
8 months ago
Hmm, I'm a bit unsure about this one. The 25-hour limit per resource could be related to expert judgment or organizational process assets. I'll need to think through the differences between those concepts.
upvoted 0 times
...

Save Cancel