Papers Penn Machine Learning Benchmark
“Penn Machine Learning Benchmark” 태그가 달린 논문 3편 · 필터 해제
Data-Informed Model Complexity Metric for Optimizing Symbolic Regression Models
2025-01-29
· Nathan Haut, Zenas Huang, Adam Alessio
Choosing models from a well-fitted evolved population that generalizes beyond training data is difficult. We introduce a pragmatic method to estimate model complexity using Hessian rank for post-processing selection. Com…
Model SelectionPenn Machine Learning BenchmarkregressionSymbolic RegressionSR-Forest: A Genetic Programming based Heterogeneous Ensemble Learning Method
2023-02-07 · IEEE Transactions on Evolutionary Computation 2023 2
· Hengzhe Zhang, Aimin Zhou, Qi Chen, Bing Xue 외
Ensemble learning methods have been widely used in machine learning in recent years due to their high predictive performance. With the development of genetic programming-based symbolic regression methods, many papers beg…
Ensemble LearningPenn Machine Learning BenchmarkregressionSymbolic RegressionAn Evolutionary Forest for Regression
2021-11-20 · IEEE Transactions on Evolutionary Computation 2021 11
· Hengzhe Zhang, Aimin Zhou, Hu Zhang
Random forest (RF) is a type of ensemble-based machine learning method that has been applied to a variety of machine learning tasks in recent years. This article proposes an evolutionary approach to generate an oblique R…
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