Which Feature is More Discriminative: Clothing or Hair Color for Gender Classification?

In the given scenario, the dressing feature {'trousers', 'skirt'} is more useful and discriminative than the hair color feature {'blond', 'black'} to classify a person as male or female. This is because, traditionally, trousers are associated with males and skirts with females, making it easier to classify individuals based on this feature. On the other hand, hair color does not have a strong association with gender, and many males and females can have the same hair color.

To formalize the discriminative power or information value of a feature, we can use measures such as information gain or entropy. Information gain measures how much a feature reduces the uncertainty in the classification problem, while entropy measures the degree of randomness or uncertainty in the data. A feature with high information gain or low entropy is considered to be more discriminative and informative. Therefore, we can use these measures to compare the discriminative power of different features in a classification problem.