Which type of models are automatically created in the Hall of Fame location?

The models that are automatically created in the Hall of Fame location are typically Regression and Decision Tree-Chaid models. In the context of Pega Decisioning, the Hall of Fame is a dedicated location for storing models that have been recognized for their high performance in predictive analytics.

Regression models, which analyze the relationship between variables, are particularly useful for predicting continuous outcomes based on input features. Decision Tree-Chaid models, a type of decision tree, are designed to handle categorical variables and provide clear visual representations of the decision-making process. Both of these modeling techniques serve as foundational analytical approaches in decisioning contexts, enhancing predictive accuracy and facilitating automated model creation.

Other options like Neural Networks, Support Vector Machines, Random Forest, Logistic Regression, K-Means, and Hierarchical Clustering represent various advanced techniques and approaches but do not characterize the specific types of models that are automatically recognized and placed in the Hall of Fame for Pega Decisioning.