IBM SPSS Modeler Cookbook

Detecting potential model instability early using the Partition node and Feature Selection node

Model instability would typically be described as an issue most noticeably during the evaluation phase. Model instability usually manifests itself as a substantially stronger performance on the Train data set than on the Test data set. This bodes ill for the performance of the model on new data; in other words, it bodes ill for the practical application of the model to any business problem. Veteran data miners see this coming well before the evaluation phase, however, or at least they hope they do. The trick is to spot one of the most common causes; model instability is much more likely to occur when the same inputs are competing for the same variance ...