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Feature Engineering for Machine Learning
Feature engineering is the process of using domain knowledge to select, modify, or create features that enhance the performance of machine learning models.
Importance of Feature Engineering
Good features can dramatically improve the performance of the model, while poor features can lead to misleading results.
Techniques
- Normalization: Adjusting the range of feature values.
- Encoding Categorical Variables: Converting categories to a numerical format.
- Feature Selection: Choosing the most relevant features.
