Explain the importance of feature selection and engineering in building a Machine Learning model.
- Enhances clustering; Reduces training time
- Enhances prediction; Increases complexity
- Improves model performance; Reduces complexity
- Improves training speed; Affects accuracy negatively
Feature selection and engineering are vital for improving model performance and reducing complexity. They help in choosing the most relevant features and transforming them for optimal model learning, thus potentially increasing accuracy and efficiency.
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