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期刊名:Genetic programming and evolvable machines

缩写:GENET PROGRAM EVOL M

ISSN:1389-2576

e-ISSN:1573-7632

IF/分区:1.7/Q3

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共收录本刊相关文章索引12
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Joseph D Romano,Trang T Le,Weixuan Fu et al. Joseph D Romano et al.
Automated machine learning (AutoML) and artificial neural networks (ANNs) have revolutionized the field of artificial intelligence by yielding incredibly high-performing models to solve a myriad of inductive learning tasks. In spite of thei...
Leonardo Trujillo,Ting Hu,Nuno Lourenço et al. Leonardo Trujillo et al.
William La Cava,Jason H Moore William La Cava
Genetic programming has found recent success as a tool for learning sets of features for regression and classification. Multidimensional genetic programming is a useful variant of genetic programming for this task because it represents cand...
Jason H Moore,Randal S Olson,Yong Chen et al. Jason H Moore et al.
The process of developing new test statistics is laborious, requiring the manual development and evaluation of mathematical functions that satisfy several theoretical properties. Automating this process, hitherto not done, would greatly acc...
David J Walker David J Walker
Visualisation is an important aspect of evolutionary computation, enabling practitioners to explore the operation of their algorithms in an intuitive way and providing a better means for displaying their results to problem owners. The prese...
Nadarajen Veerapen,Gabriela Ochoa Nadarajen Veerapen
The search landscape is a common metaphor to describe the structure of computational search spaces. Different landscape metrics can be computed and used to predict search difficulty. Yet, the metaphor falls short in visualisation terms beca...