Using Evolvable Regressors to Partition Data
Joseph Alexander Brown, Daniel Ashlock · ASME Press eBooks · 2010
This manuscript examines permitting multiple populations of evolvable regressors to compete to be the best model for the largest number of data points. Competition between populations enables a natural process of specialization that implicitly partitions the data. This partitioning technique uses function-stack based regressors and has the ability to discover the natural number of clusters in a data set via a process of sub-population collapse.