Final answer:
Classes in the classification stage of data mining are defined by the analyst-selected attributes and by the output of clustering models. Systematic sampling is exemplified by the health club surveying every tenth customer. The correct option is E. By the results of a clustering model
Step-by-step explanation:
In the classification stage of data mining, classes are defined primarily by two methods: by attributes the analyst selects, known as attribute-based classification, and by the results of a clustering model, referred to as model-based classification.
Attribute-based classification involves defining classes based on specific attributes selected by the analyst that are relevant to the target application. These attributes could be hierarchical or reticulate, divisive or agglomerative, monothetic or polythetic, and qualitative or quantitative.
Model-based classification, on the other hand, utilizes the output of a clustering model to define classes. The clusters found in the model represent the classes, and these clusters are formed based on similarities in data, which can be shaped by various distance measures or statistical methods.
Considering the health club example, where membership usage is being measured, the type of sampling design used is systematic sampling. Every tenth customer is surveyed, which is a procedure consistent with this type of sampling.
The correct option is E. By the results of a clustering model