Recursive partitioning technique

In any recursive partitioning technique, power drops dramatically as we split our data into smaller and smaller groups so that, except in huge samples, the final model selected understates the actual number of useful predictors. By giving all significant predictors the opportunity to be used for splitting, RRP makes it easy to find a more complete set of relevant variables. 

Ekins, S., Balakin, K.V., Savchuk, N. and Ivanenkov, Y. (2006) Insights for human efher-a-go-go-related gene potassium channel inhibition using recursive partitioning and Kohonen and Sammon mapping techniques. Journal of Medicinal Chemistry, 49,... 

A commonly used technique for analyzing drug discovery screening data from individuals is recursive partitioning (RP), more commonly known as trees (see, for example, Blower et al., 2002). In very recent times, efforts based on multiple trees (Svetniket al., 2003) have become the method of choice, despite the additional difficulties associated with them, because of their good predictive abilities. 

Little has been reported on the use of hierarchical divisive methods for processing chemical data sets (other than the inclusion of the minimum-diameter method in some of the comparative studies mentioned above). Recursive partitioning, which is a supervised classification technique very closely related to monothetic divisive clustering, has, however, been used at the GlaxoSmithKline and Organon companies. 

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