Publisher
Springer International Publishing
Reference26 articles.
1. Baldi, P., Brunak, S., Chauvin, Y., Andersen, C.A.F., Nielsen, H.: Assessing the accuracy of prediction algorithms for classification: an overview. Bioinformatics 16(5), 412–424 (2000). https://doi.org/10.1093/bioinformatics/16.5.412
2. Benavoli, A., Corani, G., Demšar, J., Zaffalon, M.: Time for a change: a tutorial for comparing multiple classifiers through Bayesian analysis. J. Mach. Learn. Res. 18(1), 2653–2688 (2017)
3. Bentley, P.J., Lim, S.L.: Fault tolerant fusion of office sensor data using cartesian genetic programming. In: 2017 IEEE Symposium Series on Computational Intelligence (SSCI), pp. 1–8. IEEE (2017)
4. Dua, D., Graff, C.: UCI machine learning repository (2017). https://archive.ics.uci.edu/ml
5. Goldman, B.W., Punch, W.F.: Length bias and search limitations in cartesian genetic programming. In: Proceedings of the 15th Annual Conference on Genetic and Evolutionary Computation, pp. 933–940. GECCO ’13, Association for Computing Machinery, New York, NY, USA (2013)