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What is feature engineering in machine learning?

Practice Questions

Q1
What is feature engineering in machine learning?
  1. The process of selecting the best model for a dataset
  2. The process of creating new features from existing data
  3. The process of tuning hyperparameters of a model
  4. The process of evaluating model performance

Questions & Step-by-Step Solutions

What is feature engineering in machine learning?
  • Step 1: Understand that features are the input variables used by a machine learning model.
  • Step 2: Identify the existing data you have, which includes these features.
  • Step 3: Think about how you can combine or transform these existing features to create new ones.
  • Step 4: Create new features that might help the model learn better, such as calculating averages or differences.
  • Step 5: Test the new features by using them in your model and see if they improve performance.
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