Practice Feature Construction (2.5.4) - Data Wrangling and Feature Engineering

Practice: Feature Construction

Lesson 2.5.4Data Wrangling and Feature Engineering

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9 questions

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6 sample questions

Question 1.
What is feature construction?
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Think about how you could make one feature from two or more existing ones.
Question 2.
Provide an example of feature construction.
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Consider how two numeric features relate.
3Question 3.
What is the main goal of feature construction?
- To reduce data size
- To create new features for better model performance
- To eliminate noise
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Consider the relationship between features and how they improve outcomes.
4Question 4.
True or False: Aggregation means to sum up all the data points into a single metric.
- True
- False
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Think about how we simplify data analysis.
Question 5.
You are given a dataset containing monthly sales data for products over several years. Suggest two feature construction strategies to enhance your forecasting model.
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Think about how past data can lead to insights for future predictions.
Question 6.
Design a feature construction plan for a health dataset that includes various health metrics. How would you approach combining features?
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Consider metrics that represent good health benefits.

5 more questions in this section. Enroll free to practise them all.