Analytic Continued Fractions for Regression: A Memetic Algorithm Approach
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.
Code (0)
등록된 구현이 없습니다.
Tasks
BIG-bench Machine LearningregressionSymbolic RegressionMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Multiple regression techniques for modeling dates of first performances of Shakespeare-era plays
The date of the first performance of a play of Shakespeare's time must usually be guessed with reference to multiple indirect external sources, or to some aspect of the content or style of the play. Identifying these dat…
Continued fractionregressionSymbolic Regression for Space Applications: Differentiable Cartesian Genetic Programming Powered by Multi-objective Memetic Algorithms
Interpretable regression models are important for many application domains, as they allow experts to understand relations between variables from sparse data. Symbolic regression addresses this issue by searching the spac…
regressionSymbolic RegressionAutomated Search for Conjectures on Mathematical Constants using Analysis of Integer Sequences
Formulas involving fundamental mathematical constants had a great impact on various fields of science and mathematics, for example aiding in proofs of irrationality of constants. However, the discovery of such formulas h…
Continued fractionMin-Path-Tracing: A Diffraction Aware Alternative to Image Method in Ray Tracing
For more than twenty years, Ray Tracing methods have continued to improve on both accuracy and computational time aspects. However, most state-of-the-art image-based ray tracers still rely on a description of the environ…
Randomized Memetic Artificial Bee Colony Algorithm
Artificial Bee Colony (ABC) optimization algorithm is one of the recent population based probabilistic approach developed for global optimization. ABC is simple and has been showed significant improvement over other Natu…
global-optimization