What is the importance of feature engineering in machine learning?

What is the importance of feature engineering in machine learning?

Feature engineering is crucial as it helps improve model accuracy by transforming raw data into meaningful features.

Can you give me some examples of feature engineering techniques?

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

How does feature engineering impact model performance?

Effective feature engineering can significantly enhance model performance by providing relevant information and reducing noise.

Is feature engineering more important than model selection?

Both are important, but feature engineering often has a more substantial impact on the model's success.