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; Java library for P2P communication; Model fusion via Adaptive Regression by Mixing (ARM)
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References in zbMATH (referenced in 1 article , 1 standard article )
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