Tag: Wrapper Methods
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Feature Selection in Machine Learning: Techniques and Best Practices
Introduction to Feature Selection Feature selection is the process of identifying and selecting the most relevant features (or variables) from your dataset to improve your machine learning model’s performance. By focusing on the most significant inputs, you reduce model complexity, enhance interpretability, and avoid overfitting. Feature selection is a crucial step in the preprocessing phase… Read more