论文标题
分析持续的回归分数：一种模因算法方法
Analytic Continued Fractions for Regression: A Memetic Algorithm Approach
论文作者
论文摘要
我们提出了一种用于回归问题的方法，该方法采用了分析性持续分数作为一种新的表示。在这项工作中报告了使用模因算法的比较计算结果。我们的实验包括其他15种不同的机器学习方法，包括五种用于符号回归的遗传编程方法和十种机器学习方法。使用宾夕法尼亚州立机器学习基准的94个数据集进行了训练和测试概括的比较。统计检验表明，使用分析的持续分数的概括结果为寻求紧凑且可解释的数学模型的人工智能提供了强大而有趣的新替代方案。
We present an approach for regression problems that employs analytic continued fractions as a novel representation. Comparative computational results using a memetic algorithm are reported in this work. Our experiments included fifteen other different machine learning approaches including five genetic programming methods for symbolic regression and ten machine learning methods. The comparison on training and test generalization was performed using 94 datasets of the Penn State Machine Learning Benchmark. The statistical tests showed that the generalization results using analytic continued fractions provides a powerful and interesting new alternative in the quest for compact and interpretable mathematical models for artificial intelligence.
