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In a case study involving predicting house prices, which feature would be most r
In a case study involving predicting house prices, which feature would be most relevant?
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Practice Questions
1 question
Q1
In a case study involving predicting house prices, which feature would be most relevant?
The color of the house
The number of bedrooms
The owner's name
The year the house was built
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The number of bedrooms is a relevant feature that can significantly impact house prices in a predictive model.
Questions & Step-by-step Solutions
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Q
Q: In a case study involving predicting house prices, which feature would be most relevant?
Solution:
The number of bedrooms is a relevant feature that can significantly impact house prices in a predictive model.
Steps: 4
Show Steps
Step 1: Understand that house prices can be influenced by various factors.
Step 2: Identify features that might affect house prices, such as location, size, and number of bedrooms.
Step 3: Recognize that the number of bedrooms is a key feature because more bedrooms often mean a higher price.
Step 4: Conclude that in a predictive model for house prices, the number of bedrooms is a relevant feature.
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