How would you handle a scenario where the feature values in a classification problem are on different scales?
- Apply feature scaling techniques like normalization or standardization
- Convert all features to binary values
- Ignore the scales
- Remove features with different scales
Applying feature scaling techniques like normalization or standardization ensures that all feature values are on the same scale. This is crucial for many classification algorithms, as it allows them to perform more effectively and converge faster.
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