What is feature engineering in machine learning?

What is feature engineering in machine learning?

Feature engineering is the process of using domain knowledge to select, modify, or create features that improve model performance.

Why is feature engineering important?

It's crucial because the right features can significantly enhance the predictive power of your model, leading to better results.

Can you give me some examples of feature engineering techniques?

Sure! Common techniques include normalization, one-hot encoding, and creating interaction features.

How do I know which features to engineer?

You can analyze feature importance, use domain knowledge, and experiment with different features to see their impact on model performance.