What is feature engineering in the context of machine learning?

Practice Questions

Q1
What is feature engineering in the context of 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 evaluating model performance
  4. The process of tuning hyperparameters

Questions & Step-by-Step Solutions

What is feature engineering in the context of machine learning?
  • Step 1: Understand that features are the pieces of information used by a machine learning model to make predictions.
  • Step 2: Recognize that feature engineering is the process of taking existing data and transforming it into new features.
  • Step 3: Create new features by combining, modifying, or extracting information from the original data.
  • Step 4: Use these new features to help the machine learning model learn better and make more accurate predictions.
  • Step 5: Evaluate the model's performance to see if the new features improve its accuracy.
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