Which is an example of Traditional statistical classification models?

Linear Regression serves as a classical statistical modeling technique primarily associated with prediction rather than direct classification tasks. However, your selection aligns with the broader concept of traditional statistical approaches.

In the context of classification models, the focus is often on determining which category an instance belongs to based on input features. Techniques like CHAID and C5, which represent decision tree algorithms, are indeed traditional classification methods. CHAID stands for Chi-squared Automatic Interaction Detection, making use of statistical tests to identify and split the data based on input variables effectively. C5 is an algorithm related to decision tree generation that also falls within the realm of traditional statistical methods.

Neural Nets, while powerful for classification, are generally categorized under the realm of machine learning and are non-parametric techniques. They differ fundamentally in approach and application from traditional statistical methods, which predominantly rely on established theories of probability and distribution.

Although linear regression is significant in understanding relationships between variables, it is typically not classified under standard classification models because its primary use is to predict continuous outcomes rather than discrete class labels. Hence, while it's recognized in statistical modeling, it does not fit neatly into the classification methodologies addressed by the other choices.