You are classifying patients using features: Age (numeric), Blood Pressure (numeric), and Blood Type (categorical: A, B, AB, O). Standard Euclidean distance cannot handle this mixed data. Which approach is most appropriate for designing a KNN solution?

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Assign arbitrary numeric codes (A=1, B=2, AB=3, O=4) and use Euclidean distance

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Remove the categorical feature and use only the numeric ones

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One-hot encode Blood Type and use standard Euclidean distance on everything

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Use a composite distance: normalised Euclidean for numeric features and Hamming distance for categorical features, combined with appropriate weighting

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You are classifying patients using features: Age (numeric), Blood Pressure (nume...

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