Evolutionary Regression and Modelling
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-3814-8_5
Reference89 articles.
1. Al-Helali, B.: Genetic programming for symbolic regression on incomplete data. PhD thesis, Open Access Te Herenga Waka-Victoria University of Wellington (2021)
2. Al-Helali, B., Chen, Q., Xue, B., Zhang, M.: A hybrid GP-KNN imputation for symbolic regression with missing values. In: Australasian Joint Conference on Artificial Intelligence, pp. 345–357. Springer (2018)
3. Al-Helali, B., Chen, Q., Xue, B., Zhang, M.: Genetic programming-based simultaneous feature selection and imputation for symbolic regression with incomplete data. In: Asian Conference on Pattern Recognition, pp. 566–579. Springer (2019)
4. Al-Helali, B., Chen, Q., Xue, B., Zhang, M.: GP-based feature selection and weighted KNN-based instance selection for symbolic regression with incomplete data. In: 2020 IEEE Symposium Series on Computational Intelligence (SSCI), pp. 905–912 (2020)
5. Al-Helali, B., Chen, Q., Xue, B., Zhang, M.: Hessian complexity measure for genetic programming-based imputation predictor selection in symbolic regression with incomplete data. In: European Conference on Genetic Programming (EuroGP), pp. 1–17. Springer (2020)
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