{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T13:20:34Z","timestamp":1753881634306,"version":"3.41.2"},"reference-count":27,"publisher":"World Scientific Pub Co Pte Ltd","issue":"01","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Patt. Recogn. Artif. Intell."],"published-print":{"date-parts":[[2022,1]]},"abstract":"<jats:p> In recent years, machine learning models have achieved magnificent success in many industrial applications, but most of them are black boxes. It is crucial to understand why such predictions are made in many critical areas such as medicine, financial markets, and auto driving. In this paper, we propose Coco, a novel interpretation method which can interpret any binary classifier by assigning each feature an importance value for a particular prediction. We first adopt MixUp method to generate reasonable perturbations, then apply these perturbations with constraints to obtain counterfactual instances and finally compute a comprehensive metric on these instances to estimate the importance of each feature. To demonstrate the effectiveness of Coco, we conduct extensive experiments on several datasets. The results show our method achieves better performance in identifying the most important features compared with the state-of-the-art interpretation methods, including Shap and Lime. <\/jats:p>","DOI":"10.1142\/s0218001422510016","type":"journal-article","created":{"date-parts":[[2021,12,13]],"date-time":"2021-12-13T12:52:20Z","timestamp":1639399940000},"source":"Crossref","is-referenced-by-count":1,"title":["Interpreting Model Predictions with Constrained Perturbation and Counterfactual Instances"],"prefix":"10.1142","volume":"36","author":[{"given":"Jun-Peng","family":"Fang","sequence":"first","affiliation":[{"name":"Ant Group, Hangzhou 310000, P. R. China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6033-6102","authenticated-orcid":false,"given":"Jun","family":"Zhou","sequence":"additional","affiliation":[{"name":"Zhejiang University, No. 38 Zheda Road, Hangzhou 310027, P. R. China"},{"name":"Ant Group, Hangzhou 310000, P. R. China"}]},{"given":"Qing","family":"Cui","sequence":"additional","affiliation":[{"name":"Ant Group, Hangzhou 310000, P. R. China"}]},{"given":"Cai-Zhi","family":"Tang","sequence":"additional","affiliation":[{"name":"Ant Group, Hangzhou 310000, P. R. China"}]},{"given":"Long-Fei","family":"Li","sequence":"additional","affiliation":[{"name":"Ant Group, Hangzhou 310000, P. R. China"}]}],"member":"219","published-online":{"date-parts":[[2021,12,13]]},"reference":[{"key":"S0218001422510016BIB001","first-page":"265","volume-title":"12th USENIX Symp. Operating Systems Design and Implementation (OSDI 16)","author":"Abadi M.","year":"2016"},{"key":"S0218001422510016BIB002","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2870052"},{"key":"S0218001422510016BIB004","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939785"},{"key":"S0218001422510016BIB005","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2016.42"},{"key":"S0218001422510016BIB006","doi-asserted-by":"publisher","DOI":"10.1561\/2000000039"},{"key":"S0218001422510016BIB007","doi-asserted-by":"publisher","DOI":"10.1145\/3359786"},{"key":"S0218001422510016BIB009","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpdc.2004.03.020"},{"key":"S0218001422510016BIB012","doi-asserted-by":"publisher","DOI":"10.1145\/3236009"},{"key":"S0218001422510016BIB013","first-page":"3146","volume-title":"Advances in Neural Information Processing Systems","author":"Ke G.","year":"2017"},{"key":"S0218001422510016BIB014","first-page":"659","volume-title":"Advances in Neural Information Processing Systems","author":"Kim S.-J.","year":"2006"},{"key":"S0218001422510016BIB015","series-title":"Conf. Track Proc.","volume-title":"3rd Int. Conf. Learning Representations, ICLR 2015","author":"Kingma D. P.","year":"2015"},{"key":"S0218001422510016BIB016","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-91473-2_9"},{"key":"S0218001422510016BIB017","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"S0218001422510016BIB019","first-page":"4765","volume-title":"Advances in Neural Information Processing Systems 30","author":"Lundberg S. M.","year":"2017"},{"key":"S0218001422510016BIB020","doi-asserted-by":"publisher","DOI":"10.1016\/j.artint.2018.07.007"},{"volume-title":"Interpretable Machine Learning","year":"2020","author":"Molnar C.","key":"S0218001422510016BIB021"},{"key":"S0218001422510016BIB023","doi-asserted-by":"publisher","DOI":"10.1016\/j.dsp.2017.10.011"},{"key":"S0218001422510016BIB024","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-29908-8_4"},{"key":"S0218001422510016BIB025","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2014.6854318"},{"key":"S0218001422510016BIB027","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939778"},{"key":"S0218001422510016BIB028","first-page":"1527","volume-title":"Proc. AAAI Conf. Artificial Intelligence","volume":"32","author":"Ribeiro M. T.","year":"2018"},{"key":"S0218001422510016BIB029","volume":"24","author":"Saabas A.","year":"2014","journal-title":"Diving into data"},{"key":"S0218001422510016BIB031","first-page":"3319","volume-title":"Int. Conf. Machine Learning","author":"Sundararajan M.","year":"2017"},{"key":"S0218001422510016BIB033","doi-asserted-by":"publisher","DOI":"10.1109\/RT.2006.280216"},{"key":"S0218001422510016BIB034","doi-asserted-by":"publisher","DOI":"10.1109\/CIDM.2009.4938667"},{"key":"S0218001422510016BIB035","series-title":"Conference Track Proceedings","volume-title":"6th International Conference on Learning Representations, (ICLR) 2018","author":"Zhang H.","year":"2018"},{"key":"S0218001422510016BIB036","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2016.04.001"}],"container-title":["International Journal of Pattern Recognition and Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0218001422510016","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,3,3]],"date-time":"2022-03-03T07:58:25Z","timestamp":1646294305000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S0218001422510016"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12,13]]},"references-count":27,"journal-issue":{"issue":"01","published-print":{"date-parts":[[2022,1]]}},"alternative-id":["10.1142\/S0218001422510016"],"URL":"https:\/\/doi.org\/10.1142\/s0218001422510016","relation":{},"ISSN":["0218-0014","1793-6381"],"issn-type":[{"type":"print","value":"0218-0014"},{"type":"electronic","value":"1793-6381"}],"subject":[],"published":{"date-parts":[[2021,12,13]]},"article-number":"2251001"}}