Skiers are faced with an ever-growing number of alpine skis to choose from. To simplify the shopping process, skis are divided into categories based on their intended usage. However, these categories are loosely defined, with numerous categorizations available. This paper presents a methodology based on decision trees to investigate how alpine skis are currently classified by the ski industry. As an example, simple, robust, and clear classification rules have been identified from the categories used by a large retailer. The rules found are only based on the measured physical attributes of the skis. Decision trees identified a few classification rules, three or fewer in all but one case, that provide high accuracy (88-97.5%) and inclusiveness (85-100%, except for the All-Mountain category). The rules found are easy to interpret by most skiers, especially when analyzing the other attributes highly correlated with each splitting rule of the decision trees. The rules found could be used by retailers to classify skis from different brands uniformly and automatically. Such rules could also be used to educate customers and simplify their shopping experience.
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