Using Evolvable Regressors to Partition Data


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.

  • Abstract
  • 1 Introduction
  • 2 Methods
  • 3 Results and Discussion
  • 4 Conclusion
  • Acknowledgements
  • References

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