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Exam AI-900 topic 1 question 41 discussion

Actual exam question from Microsoft's AI-900

Question #: 41
Topic #: 1

HOTSPOT -
You have the following dataset.

You plan to use the dataset to train a model that will predict the house price categories of houses.
What are Household Income and House Price Category? To answer, select the appropriate option in the answer area.
NOTE: Each correct selection is worth one point.
Hot Area:

Show Suggested Answer

Suggested Answer:

Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio/interpret-model-results

by ExamTopics007 at Dec. 2, 2020, 1:44 a.m.

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Joe75

Highly Voted 4 years ago

correct. Feature = Input. Label = Output.

upvoted 41 times

PXAbstraction

12 months ago

This is such a simple trick to remembering this and it was never once mentioned in the course I took to prepare for this. Thank you!

upvoted 2 times

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ipindado2020

Highly Voted 4 years, 6 months ago

answer is correct

upvoted 13 times

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saema

Most Recent 5 months, 1 week ago

a feature a label

upvoted 1 times

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gina_the_boss

11 months ago

On exam Jul 26, 2024

upvoted 4 times

Thomas90sr

10 months, 3 weeks ago

I love you

upvoted 2 times

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[Removed]

1 year, 5 months ago

On exam 08/01/2024

upvoted 2 times

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Shri0506

1 year, 5 months ago

in exam 29 Dec 2023

upvoted 2 times

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Vanessa23

1 year, 7 months ago

Feature / Label

upvoted 1 times

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vini23

1 year, 9 months ago

This question appeared in Exam on 9/17/23

upvoted 1 times

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AzlearnRB

1 year, 11 months ago

on exam july 2023

upvoted 2 times

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zellck

2 years ago

1. feature 2. label https://learn.microsoft.com/en-us/training/modules/create-regression-model-azure-machine-learning-designer/2-regression-scenarios Regression is a form of machine learning used to understand the relationships between variables to predict a desired outcome. Regression predicts a numeric label or outcome based on variables, or features. For example, an automobile sales company might use the characteristics of a car (such as engine size, number of seats, mileage, and so on) to predict its likely selling price. In this case, the characteristics of the car are the features, and the selling price is the label.

upvoted 1 times