2.5.2 - Feature Transformation
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Practice Questions
Test your understanding with targeted questions
What is feature transformation?
💡 Hint: Think about how we modify features before they go into a model.
Name a scaling method used in feature transformation.
💡 Hint: One method rescales to a specific range, and the other standardizes.
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Interactive Quizzes
Quick quizzes to reinforce your learning
What is the purpose of feature transformation?
💡 Hint: Remember why we manipulate data before applying any algorithms.
True or False: Scaling feature values can lead to more accurate model predictions.
💡 Hint: Consider why models might behave differently with varied scale features.
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Challenge Problems
Push your limits with advanced challenges
You are given a dataset with multiple features, some exhibiting strong skewness. Outline a step-by-step approach to handle these features for a regression model.
💡 Hint: Consider both transformation and scaling as critical components.
Imagine you are tasked with preparing a dataset with features ranging from 1 to 1000 versus features from 0 to 1 for a machine learning model. Describe how you would unify these features.
💡 Hint: How do scaling methods equalize varying feature ranges?
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