What is a segmentation modeling method that automatically determines the number of clusters?

The correct choice is TwoStep, as it is a segmentation modeling method specifically designed to handle large datasets and automatically determines the optimal number of clusters. This method assesses the data and generates clusters based on both categorical and continuous data types, creating a model that can effectively identify patterns and groupings in the data without requiring the user to predefine the number of clusters.

TwoStep operates by using a two-phase clustering process, where the first phase builds a cluster feature tree, which can streamline computations significantly and allow for efficient analysis, especially with large datasets. Then in the second phase, it assigns each record to the nearest cluster, refining the clusters identified in the initial phase. This automatic determination of cluster numbers is essential in exploratory data analysis and prevents user bias or arbitrary cluster number choices that could lead to misleading results.

Other methods like AutoCluster may have some automatic features but don't necessarily guarantee the effectiveness or suitability of the clusters identified across diverse datasets. Kohonen networks are a type of neural network used for clustering but are not primarily designed to determine the number of clusters autonomously. K-Means, on the other hand, requires the user to specify the number of clusters beforehand, making it less flexible for scenarios where the optimal cluster number is unknown. Therefore, Two