FlexGP: Flexible ML with Genetic Programming
The FlexGP framework
FlexGP exploits the multi-level parallelism of GP to tackle large regression problems. FlexGP is composed of a sophisticated learner, a set of launch scripts, and a Java library that provides a TCP/IP communication layer:
- Multiple Regression Genetic Programming (MRGP) learner
- Decentralized launch protocol
- The Java library for P2P communication
- Model fusion via Adaptive Regression by Mixing (ARM)
Running FlexGP on Amazon EC2
Veeramachaneni, K; Arnaldo, I; Derby, O; O’Reilly, UM: FlexGP: Cloud-Based Ensemble Learning with Genetic Programming for Large Regression Problems. Journal of Grid Computing. November, 2014.
FlexGP is a project of the Any-Scale Learning For All (ALFA) group at MIT.
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