P11Feature EngineeringIntermediateInterpret10 min
Should You Scale Features Before KNN?
Decide whether scaling is necessary when distance drives a model's predictions.
#KNN#feature scaling#distance
Scenario
A K-nearest-neighbors model predicts customer segments using annual income in dollars and website visits per month.
Problem statement
Explain whether to scale the features before KNN and why, including one important caveat about the pipeline.
Your Task
- Compare the raw feature scales.
- Explain how distance is affected.
- Describe where scaling belongs when evaluating the model.
Feature ranges
annual_income: 25,000 to 250,000
monthly_visits: 0 to 90
Related Concepts
StandardizationPipelinesData leakage
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