{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T12:49:31Z","timestamp":1782478171030,"version":"3.54.5"},"publisher-location":"New York, NY, USA","reference-count":35,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,6,26]],"date-time":"2021-06-26T00:00:00Z","timestamp":1624665600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo (FAPESP)","award":["2018\/14173-8"],"award-info":[{"award-number":["2018\/14173-8"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,6,26]]},"DOI":"10.1145\/3449639.3459302","type":"proceedings-article","created":{"date-parts":[[2021,6,21]],"date-time":"2021-06-21T17:50:43Z","timestamp":1624297843000},"page":"750-758","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":11,"title":["Measuring feature importance of symbolic regression models using partial effects"],"prefix":"10.1145","author":[{"given":"Guilherme Seidyo Imai","family":"Aldeia","sequence":"first","affiliation":[{"name":"Universidade Federal do ABC, Santo Andr\u00e9, SP, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fabr\u00edcio Olivetti","family":"de Fran\u00e7a","sequence":"additional","affiliation":[{"name":"Universidade Federal do ABC, Santo Andr\u00e9, SP, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2021,6,26]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Interpreting and using regression","author":"Achen Christopher H","unstructured":"Christopher H Achen . 1982. Interpreting and using regression . Vol. 29 . Sage . Christopher H Achen. 1982. Interpreting and using regression. Vol. 29. Sage."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4939-0375-7_10"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1111\/stan.12130"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/cec48606.2020.9185521"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/cec.2018.8477951"},{"key":"e_1_3_2_1_6_1","volume-title":"Jaakkola","author":"Alvarez-Melis David","year":"2018","unstructured":"David Alvarez-Melis and Tommi S . Jaakkola . 2018 . On the Robustness of Interpretability Methods. CoRR abs\/1806.08049 (2018), 6. arXiv:1806.08049 http:\/\/arxiv.org\/abs\/1806.08049 David Alvarez-Melis and Tommi S. Jaakkola. 2018. On the Robustness of Interpretability Methods. CoRR abs\/1806.08049 (2018), 6. arXiv:1806.08049 http:\/\/arxiv.org\/abs\/1806.08049"},{"key":"e_1_3_2_1_7_1","volume-title":"Can I Trust the Explainer? Verifying Post-hoc Explanatory Methods. CoRR abs\/1910.02065","author":"Camburu Oana-Maria","year":"2019","unstructured":"Oana-Maria Camburu , Eleonora Giunchiglia , Jakob Foerster , Thomas Lukasiewicz , and Phil Blunsom . 2019. Can I Trust the Explainer? Verifying Post-hoc Explanatory Methods. CoRR abs\/1910.02065 ( 2019 ), 13. arXiv:1910.02065 http:\/\/arxiv.org\/abs\/1910.02065 Oana-Maria Camburu, Eleonora Giunchiglia, Jakob Foerster, Thomas Lukasiewicz, and Phil Blunsom. 2019. Can I Trust the Explainer? Verifying Post-hoc Explanatory Methods. CoRR abs\/1910.02065 (2019), 13. arXiv:1910.02065 http:\/\/arxiv.org\/abs\/1910.02065"},{"key":"e_1_3_2_1_8_1","unstructured":"Oana-Maria Camburu Eleonora Giunchiglia Jakob Foerster Thomas Lukasiewicz and Phil Blunsom. 2020. The Struggles of Feature-Based Explanations: Shapley Values vs. Minimal Sufficient Subsets. arXiv:2009.11023 [cs.CL]  Oana-Maria Camburu Eleonora Giunchiglia Jakob Foerster Thomas Lukasiewicz and Phil Blunsom. 2020. The Struggles of Feature-Based Explanations: Shapley Values vs. Minimal Sufficient Subsets. arXiv:2009.11023 [cs.CL]"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2788613"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1162\/evco_a_00285"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2020.10.062"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/cec48606.2020.9185620"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/cec48606.2020.9185683"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3236009"},{"key":"e_1_3_2_1_15_1","volume-title":"Advances in Neural Information Processing Systems, H. Wallach, H. Larochelle, A. Beygelzimer, F. d'Alch\u00e9-Buc","author":"Hooker Sara","year":"2019","unstructured":"Sara Hooker , Dumitru Erhan , Pieter-Jan Kindermans , and Been Kim . 2019. A Benchmark for Interpretability Methods in Deep Neural Networks . In Advances in Neural Information Processing Systems, H. Wallach, H. Larochelle, A. Beygelzimer, F. d'Alch\u00e9-Buc , E. Fox, and R. Garnett (Eds.), Vol. 32 . Curran Associates, Inc. , Red Hook, NY, USA , 9737--9748. https:\/\/proceedings.neurips.cc\/paper\/ 2019 \/file\/fe4b8556000d0f0cae99daa5c5c5a410-Paper.pdf Sara Hooker, Dumitru Erhan, Pieter-Jan Kindermans, and Been Kim. 2019. A Benchmark for Interpretability Methods in Deep Neural Networks. In Advances in Neural Information Processing Systems, H. Wallach, H. Larochelle, A. Beygelzimer, F. d'Alch\u00e9-Buc, E. Fox, and R. Garnett (Eds.), Vol. 32. Curran Associates, Inc., Red Hook, NY, USA, 9737--9748. https:\/\/proceedings.neurips.cc\/paper\/2019\/file\/fe4b8556000d0f0cae99daa5c5c5a410-Paper.pdf"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10710-019-09371-3"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/388"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1069362310"},{"key":"e_1_3_2_1_19_1","volume-title":"Proceedings of the 31st International Conference on Neural Information Processing Systems","author":"Scott","unstructured":"Scott M. Lundberg and Su-In Lee. 2017. A Unified Approach to Interpreting Model Predictions . In Proceedings of the 31st International Conference on Neural Information Processing Systems ( Long Beach, California, USA) (NIPS'17). Curran Associates Inc., Red Hook, NY, USA, 4768--4777. Scott M. Lundberg and Su-In Lee. 2017. A Unified Approach to Interpreting Model Predictions. In Proceedings of the 31st International Conference on Neural Information Processing Systems (Long Beach, California, USA) (NIPS'17). Curran Associates Inc., Red Hook, NY, USA, 4768--4777."},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1177\/0081175019852763"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2019.1954"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2018.02.040"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1007\/s40273-014-0210-6"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/3205455.3205539"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N16-3020"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939778"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"crossref","unstructured":"Cynthia Rudin. 2018. Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead. arXiv:1811.10154 [stat.ML]  Cynthia Rudin. 2018. Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead. arXiv:1811.10154 [stat.ML]","DOI":"10.1038\/s42256-019-0048-x"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/cbms.2019.00065"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-34223-8_14"},{"key":"e_1_3_2_1_30_1","volume-title":"Explaining prediction models and individual predictions with feature contributions. Knowledge and information systems 41, 3","author":"\u0160trumbelj Erik","year":"2014","unstructured":"Erik \u0160trumbelj and Igor Kononenko . 2014. Explaining prediction models and individual predictions with feature contributions. Knowledge and information systems 41, 3 ( 2014 ), 647--665. Erik \u0160trumbelj and Igor Kononenko. 2014. Explaining prediction models and individual predictions with feature contributions. Knowledge and information systems 41, 3 (2014), 647--665."},{"key":"e_1_3_2_1_31_1","volume-title":"International Conference on Machine Learning. PMLR, 9269--9278","author":"Sundararajan Mukund","year":"2020","unstructured":"Mukund Sundararajan and Amir Najmi . 2020 . The many Shapley values for model explanation . In International Conference on Machine Learning. PMLR, 9269--9278 . Mukund Sundararajan and Amir Najmi. 2020. The many Shapley values for model explanation. In International Conference on Machine Learning. PMLR, 9269--9278."},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1126\/sciadv.aay2631"},{"key":"e_1_3_2_1_33_1","unstructured":"Mengjiao Yang and Been Kim. 2019. Benchmarking Attribution Methods with Relative Feature Importance. arXiv:1907.09701 [cs.LG]  Mengjiao Yang and Been Kim. 2019. Benchmarking Attribution Methods with Relative Feature Importance. arXiv:1907.09701 [cs.LG]"},{"key":"e_1_3_2_1_34_1","volume-title":"BIM: Towards Quantitative Evaluation of Interpretability Methods with Ground Truth. CoRR abs\/1907.09701","author":"Yang Mengjiao","year":"2019","unstructured":"Mengjiao Yang and Been Kim . 2019 . BIM: Towards Quantitative Evaluation of Interpretability Methods with Ground Truth. CoRR abs\/1907.09701 (2019), 17. arXiv:1907.09701 http:\/\/arxiv.org\/abs\/1907.09701 Mengjiao Yang and Been Kim. 2019. BIM: Towards Quantitative Evaluation of Interpretability Methods with Ground Truth. CoRR abs\/1907.09701 (2019), 17. arXiv:1907.09701 http:\/\/arxiv.org\/abs\/1907.09701"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1080\/07350015.2019.1624293"}],"event":{"name":"GECCO '21: Genetic and Evolutionary Computation Conference","location":"Lille France","acronym":"GECCO '21","sponsor":["SIGEVO ACM Special Interest Group on Genetic and Evolutionary Computation"]},"container-title":["Proceedings of the Genetic and Evolutionary Computation Conference"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3449639.3459302","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3449639.3459302","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T21:28:08Z","timestamp":1750195688000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3449639.3459302"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,6,26]]},"references-count":35,"alternative-id":["10.1145\/3449639.3459302","10.1145\/3449639"],"URL":"https:\/\/doi.org\/10.1145\/3449639.3459302","relation":{},"subject":[],"published":{"date-parts":[[2021,6,26]]},"assertion":[{"value":"2021-06-26","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}