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What are quantitative data and category data?
Quantitative data is to express some uncertain and fuzzy factors with specific data, and to reflect the state of nature or society with linear transformation data within a certain range, so as to achieve the purpose of analysis and comparison.

Category data is data that reflects the type of things by classifying or grouping phenomena according to certain attributes, also known as category data. In order to facilitate computer processing, digital codes are usually used to represent various categories, such as 1 for "male" and 0 for "female", but 1 and 0 are only data codes, and there is no quantitative relationship or difference between them.

Extended data:

Category data is clearly interpreted by users or experts at the schema level: usually, the conceptual hierarchy of classification attributes or dimensions involves a set of attributes. Users or experts can easily define the concept hierarchy by explaining the partial order or full order of pattern-level attributes.

Defining the number of different values for each attribute in an attribute set automatically generates a conceptual hierarchy. The attribute with the largest difference value is placed at the lowest level in the hierarchy. The fewer the number of different values of an attribute, the higher its position in the generated conceptual hierarchy. In many cases, this heuristic rule is very useful.

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