{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T03:40:40Z","timestamp":1740109240452,"version":"3.37.3"},"reference-count":87,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2024,5,30]],"date-time":"2024-05-30T00:00:00Z","timestamp":1717027200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,5,30]],"date-time":"2024-05-30T00:00:00Z","timestamp":1717027200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["2107290"],"award-info":[{"award-number":["2107290"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["The VLDB Journal"],"published-print":{"date-parts":[[2024,7]]},"DOI":"10.1007\/s00778-024-00857-w","type":"journal-article","created":{"date-parts":[[2024,5,30]],"date-time":"2024-05-30T09:45:49Z","timestamp":1717062349000},"page":"1203-1230","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Reliability evaluation of individual predictions: a data-centric approach"],"prefix":"10.1007","volume":"33","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7016-3807","authenticated-orcid":false,"given":"Nima","family":"Shahbazi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Abolfazl","family":"Asudeh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,5,30]]},"reference":[{"key":"857_CR1","doi-asserted-by":"crossref","unstructured":"Abdar, M., Pourpanah, F., Hussain, S., Rezazadegan, D., Liu, L., Ghavamzadeh, M., Fieguth, P., Cao, X., Khosravi, A., Acharya, U.R., Makarenkov, V., Nahavandi, S.: A review of uncertainty quantification in deep learning: Techniques, applications and challenges. Information Fusion pp. 243\u2013297 (2021)","DOI":"10.1016\/j.inffus.2021.05.008"},{"key":"857_CR2","unstructured":"Accinelli, C., Catania, B., Guerrini, G., Minisi, S.: The impact of rewriting on coverage constraint satisfaction. In: EDBT\/ICDT Workshops (2021)"},{"key":"857_CR3","unstructured":"Accinelli, C., Minisi, S., Catania, B.: Coverage-based rewriting for data preparation. In: EDBT\/ICDT Workshops (2020)"},{"issue":"3","key":"857_CR4","doi-asserted-by":"publisher","first-page":"654","DOI":"10.1137\/S0097539795281840","volume":"27","author":"PK Agarwal","year":"1998","unstructured":"Agarwal, P.K., De Berg, M., Matousek, J., Schwarzkopf, O.: Constructing levels in arrangements and higher order Voronoi diagrams. SIAM J. Comput. 27(3), 654\u2013667 (1998)","journal-title":"SIAM J. Comput."},{"key":"857_CR5","unstructured":"Agarwal, P.K., Kumar, N., Sintos, S., Suri, S.: Efficient algorithms for k-regret minimizing sets. LIPIcs (2017)"},{"key":"857_CR6","unstructured":"Agrawal, S.: Diamonds (2017). https:\/\/www.kaggle.com\/datasets\/shivam2503\/diamonds"},{"key":"857_CR7","unstructured":"Angelopoulos, A.N., Bates, S.: A gentle introduction to conformal prediction and distribution-free uncertainty quantification. CoRR (2021)"},{"key":"857_CR8","doi-asserted-by":"crossref","unstructured":"Asudeh, A., Jagadish, H., Stoyanovich, J., Das, G.: Designing fair ranking schemes. In: SIGMOD, pp. 1259\u20131276 (2019)","DOI":"10.1145\/3299869.3300079"},{"key":"857_CR9","doi-asserted-by":"crossref","unstructured":"Asudeh, A., Jin, Z., Jagadish, H.: Assessing and remedying coverage for a given dataset. In: ICDE, pp. 554\u2013565. IEEE (2019)","DOI":"10.1109\/ICDE.2019.00056"},{"key":"857_CR10","doi-asserted-by":"crossref","unstructured":"Asudeh, A., Shahbazi, N., Jin, Z., Jagadish, H.: Identifying insufficient data coverage for ordinal continuous-valued attributes. In: SIGMOD, pp. 129\u2013141 (2021)","DOI":"10.1145\/3448016.3457315"},{"issue":"2","key":"857_CR11","doi-asserted-by":"publisher","first-page":"467","DOI":"10.1016\/j.jue.2007.03.001","volume":"63","author":"L Blanchard","year":"2008","unstructured":"Blanchard, L., Zhao, B., Yinger, J.: Do lenders discriminate against minority and woman entrepreneurs? J. Urban Econ. 63(2), 467\u2013497 (2008)","journal-title":"J. Urban Econ."},{"key":"857_CR12","unstructured":"Blundell, C., Cornebise, J., Kavukcuoglu, K., Wierstra, D.: Weight uncertainty in neural network. In: ICML, pp. 1613\u20131622 (2015)"},{"key":"857_CR13","doi-asserted-by":"crossref","unstructured":"Bohler, C., Cheilaris, P., Klein, R., Liu, C.H., Papadopoulou, E., Zavershynskyi, M.: On the complexity of higher order abstract Voronoi diagrams. In: International Colloquium on Automata, Languages, and Programming, pp. 208\u2013219. Springer (2013)","DOI":"10.1007\/978-3-642-39206-1_18"},{"issue":"3","key":"857_CR14","doi-asserted-by":"publisher","first-page":"504","DOI":"10.1016\/j.datak.2008.08.001","volume":"67","author":"Z Bosni\u0107","year":"2008","unstructured":"Bosni\u0107, Z., Kononenko, I.: Comparison of approaches for estimating reliability of individual regression predictions. Data Knowl. Eng. 67(3), 504\u2013516 (2008)","journal-title":"Data Knowl. Eng."},{"key":"857_CR15","doi-asserted-by":"publisher","DOI":"10.1201\/9781315139470","volume-title":"Classification and Regression Trees","author":"L Breiman","year":"2017","unstructured":"Breiman, L., Friedman, J.H., Olshen, R.A., Stone, C.J.: Classification and Regression Trees. Routledge, London (2017)"},{"key":"857_CR16","doi-asserted-by":"crossref","unstructured":"Breunig, M.M., Kriegel, H.P., Ng, R.T., Sander, J.: LOF: identifying density-based local outliers. In: SIGMOD, pp. 93\u2013104 (2000)","DOI":"10.1145\/335191.335388"},{"issue":"1","key":"857_CR17","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1175\/1520-0493(1950)078<0001:VOFEIT>2.0.CO;2","volume":"78","author":"GW Brier","year":"1950","unstructured":"Brier, G.W., et al.: Verification of forecasts expressed in terms of probability. Mon. Weather Rev. 78(1), 1\u20133 (1950)","journal-title":"Mon. Weather Rev."},{"key":"857_CR18","unstructured":"Butler, A.W., Mayer, E.J., Weston, J.: Racial discrimination in the auto loan market. Available at SSRN (2020)"},{"key":"857_CR19","unstructured":"Carlini, N., Erlingsson, U., Papernot, N.: Distribution density, tails, and outliers in machine learning: Metrics and applications. CoRR (2019)"},{"issue":"3","key":"857_CR20","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1541880.1541882","volume":"41","author":"V Chandola","year":"2009","unstructured":"Chandola, V., Banerjee, A., Kumar, V.: Anomaly detection: a survey. CSUR 41(3), 1\u201358 (2009)","journal-title":"CSUR"},{"key":"857_CR21","doi-asserted-by":"publisher","first-page":"121","DOI":"10.1080\/07350015.1993.10509938","volume":"11","author":"C Chatfield","year":"1993","unstructured":"Chatfield, C.: Prediction intervals. J. Bus. Econ. Stat. 11, 121\u2013135 (1993)","journal-title":"J. Bus. Econ. Stat."},{"issue":"11","key":"857_CR22","doi-asserted-by":"publisher","first-page":"1349","DOI":"10.1109\/TC.1987.5009474","volume":"100","author":"B Chazelle","year":"1987","unstructured":"Chazelle, B., Edelsbrunner, H.: An improved algorithm for constructing kth-order Voronoi diagrams. IEEE Trans. Comput. 100(11), 1349\u20131354 (1987)","journal-title":"IEEE Trans. Comput."},{"key":"857_CR23","doi-asserted-by":"crossref","unstructured":"Datta, A., Sen, S., Zick, Y.: Algorithmic transparency via quantitative input influence: theory and experiments with learning systems. In: SP, pp. 598\u2013617. IEEE (2016)","DOI":"10.1109\/SP.2016.42"},{"key":"857_CR24","doi-asserted-by":"crossref","unstructured":"Dong, X.L., Gabrilovich, E., Murphy, K., Dang, V., Horn, W., Lugaresi, C., Sun, S., Zhang, W.: Knowledge-based trust: estimating the trustworthiness of web sources. CoRR (2015)","DOI":"10.14778\/2777598.2777603"},{"key":"857_CR25","doi-asserted-by":"crossref","unstructured":"Dwork, C., Hardt, M., Pitassi, T., Reingold, O., Zemel, R.: Fairness through awareness. In: ITCS, pp. 214\u2013226 (2012)","DOI":"10.1145\/2090236.2090255"},{"issue":"1","key":"857_CR26","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1007\/BF02187681","volume":"1","author":"H Edelsbrunner","year":"1986","unstructured":"Edelsbrunner, H., Seidel, R.: Voronoi diagrams and arrangements. Discr. Comput. Geom. 1(1), 25\u201344 (1986)","journal-title":"Discr. Comput. Geom."},{"key":"857_CR27","unstructured":"Ester, M., Kriegel, H.P., Sander, J., Xu, X., et\u00a0al.: A density-based algorithm for discovering clusters in large spatial databases with noise. In: KDD, pp. 226\u2013231 (1996)"},{"key":"857_CR28","doi-asserted-by":"crossref","unstructured":"Fariha, A., Tiwari, A., Radhakrishna, A., Gulwani, S., Meliou, A.: Conformance constraint discovery: Measuring trust in data-driven systems. In: SIGMOD, pp. 499-512. Association for Computing Machinery (2021)","DOI":"10.1145\/3448016.3452795"},{"key":"857_CR29","unstructured":"Gebel, M.: Multivariate calibration of classifier scores into the probability space. Ph.D. thesis, Citeseer (2009)"},{"issue":"2","key":"857_CR30","first-page":"44","volume":"40","author":"D Gunning","year":"2019","unstructured":"Gunning, D., Aha, D.: Darpa\u2019s explainable artificial intelligence (XAI) program. AI Mag. 40(2), 44\u201358 (2019)","journal-title":"AI Mag."},{"key":"857_CR31","unstructured":"Guyon, I., Gunn, S., Ben-Hur, A., Dror, G.: Result analysis of the NIPS 2003 feature selection challenge. NeurIPS 17, (2004)"},{"key":"857_CR32","unstructured":"Harlfoxem: House sales in king county, USA (2016). https:\/\/www.kaggle.com\/harlfoxem\/housesalesprediction\/"},{"key":"857_CR33","unstructured":"Harradon, M., Druce, J., Ruttenberg, B.: Causal learning and explanation of deep neural networks via autoencoded activations. CoRR (2018)"},{"key":"857_CR34","doi-asserted-by":"crossref","unstructured":"Hautamaki, V., Karkkainen, I., Franti, P.: Outlier detection using k-nearest neighbour graph. In: Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004. (2004)","DOI":"10.1109\/ICPR.2004.1334558"},{"key":"857_CR35","doi-asserted-by":"crossref","unstructured":"Jayasinghe, U., Otebolaku, A., Um, T.W., Lee, G.M.: Data centric trust evaluation and prediction framework for iot. In: ITU K, pp. 1\u20137. IEEE (2017)","DOI":"10.23919\/ITU-WT.2017.8246999"},{"key":"857_CR36","doi-asserted-by":"crossref","unstructured":"Jin, Z., Xu, M., Sun, C., Asudeh, A., Jagadish, H.: Mithracoverage: A system for investigating population bias for intersectional fairness. In: SIGMOD, pp. 2721\u20132724 (2020)","DOI":"10.1145\/3318464.3384689"},{"key":"857_CR37","unstructured":"Kakade, S.M.: On the sample complexity of reinforcement learning. University of London, University College London (United Kingdom) (2003)"},{"key":"857_CR38","doi-asserted-by":"crossref","unstructured":"Kaul, M., Yang, B., Jensen, C.S.: Building accurate 3d spatial networks to enable next generation intelligent transportation systems. In: MDM, vol.\u00a01, pp. 137\u2013146. IEEE (2013)","DOI":"10.1109\/MDM.2013.24"},{"key":"857_CR39","unstructured":"Kentour, M., Lu, J.: Analysis of trustworthiness in machine learning and deep learning. InfoComp (2021)"},{"issue":"3","key":"857_CR40","doi-asserted-by":"publisher","first-page":"337","DOI":"10.1109\/TNN.2010.2096824","volume":"22","author":"A Khosravi","year":"2010","unstructured":"Khosravi, A., Nahavandi, S., Creighton, D., Atiya, A.F.: Lower upper bound estimation method for construction of neural network-based prediction intervals. IEEE Trans. Neural Netw. 22(3), 337\u2013346 (2010)","journal-title":"IEEE Trans. Neural Netw."},{"issue":"9","key":"857_CR41","doi-asserted-by":"publisher","first-page":"1341","DOI":"10.1109\/TNN.2011.2162110","volume":"22","author":"A Khosravi","year":"2011","unstructured":"Khosravi, A., Nahavandi, S., Creighton, D., Atiya, A.F.: Comprehensive review of neural network-based prediction intervals and new advances. IEEE Trans. Neural Netw. 22(9), 1341\u20131356 (2011)","journal-title":"IEEE Trans. Neural Netw."},{"key":"857_CR42","first-page":"202","volume":"96","author":"R Kohavi","year":"1996","unstructured":"Kohavi, R., et al.: Scaling up the accuracy of naive-bayes classifiers: a decision-tree hybrid. KDD 96, 202\u2013207 (1996)","journal-title":"KDD"},{"issue":"12","key":"857_CR43","first-page":"2706","volume":"13","author":"C Kuhlman","year":"2020","unstructured":"Kuhlman, C., Rundensteiner, E.: Rank aggregation algorithms for fair consensus. VLDB 13(12), 2706\u20132719 (2020)","journal-title":"VLDB"},{"key":"857_CR44","unstructured":"Kulynych, B., Yang, Y.Y., Yu, Y., B\u0142asiok, J., Nakkiran, P.: What you see is what you get: Distributional generalization for algorithm design in deep learning. CoRR (2022)"},{"key":"857_CR45","unstructured":"LeCun, Y., Cortes, C.: MNIST handwritten digit database (2010). http:\/\/yann.lecun.com\/exdb\/mnist\/"},{"issue":"6","key":"857_CR46","first-page":"478","volume":"100","author":"DT Lee","year":"1982","unstructured":"Lee, D.T.: On k-nearest neighbor Voronoi diagrams in the plane. IEEE Trans. Comput. 100(6), 478\u2013487 (1982)","journal-title":"IEEE Trans. Comput."},{"key":"857_CR47","doi-asserted-by":"crossref","unstructured":"Lewis, D.D.: A sequential algorithm for training text classifiers: Corrigendum and additional data. In: SIGIR, pp. 13\u201319. ACM New York, NY, USA (1995)","DOI":"10.1145\/219587.219592"},{"key":"857_CR48","doi-asserted-by":"crossref","unstructured":"Li, Z., Zhao, Y., Hu, X., Botta, N., Ionescu, C., Chen, G.: Ecod: Unsupervised outlier detection using empirical cumulative distribution functions. TKDE (2022)","DOI":"10.2139\/ssrn.4313179"},{"issue":"12","key":"857_CR49","first-page":"2229","volume":"13","author":"Y Lin","year":"2020","unstructured":"Lin, Y., Guan, Y., Asudeh, A., Jagadish, H.: Identifying insufficient data coverage in databases with multiple relations. VLDB 13(12), 2229\u20132242 (2020)","journal-title":"VLDB"},{"key":"857_CR50","doi-asserted-by":"crossref","unstructured":"Liu, F.T., Ting, K.M., Zhou, Z.H.: Isolation forest. In: ICDM, pp. 413\u2013422. IEEE (2008)","DOI":"10.1109\/ICDM.2008.17"},{"key":"857_CR51","unstructured":"Liu, H., Wang, Y., Fan, W., Liu, X., Li, Y., Jain, S., Jain, A.K., Tang, J.: Trustworthy AI: a computational perspective. CoRR (2021)"},{"key":"857_CR52","unstructured":"Lundberg, S.M., Lee, S.I.: A unified approach to interpreting model predictions. NeurIPS 30, (2017)"},{"key":"857_CR53","unstructured":"McCallum, A.: real-sim data set. https:\/\/www.csie.ntu.edu.tw\/~cjlin\/libsvmtools\/datasets\/binary.html#real-sim"},{"key":"857_CR54","unstructured":"McCallum, A.: Sraa data set. https:\/\/people.cs.umass.edu\/~mccallum\/data.html"},{"key":"857_CR55","unstructured":"Molnar, C.: Interpretable machine learning. Lulu.com (2020)"},{"key":"857_CR56","doi-asserted-by":"crossref","unstructured":"Montoya, A.M., Parrado, E., Sol\u00eds, A., Undurraga, R.: Bad taste: gender discrimination in the consumer credit market. Tech. rep., IDB Working Paper Series (2020)","DOI":"10.18235\/0001921"},{"issue":"12","key":"857_CR57","first-page":"2829","volume":"13","author":"Y Moskovitch","year":"2020","unstructured":"Moskovitch, Y., Jagadish, H.: Countata: dataset labeling using pattern counts. VLDB 13(12), 2829\u20132832 (2020)","journal-title":"VLDB"},{"issue":"11","key":"857_CR58","doi-asserted-by":"publisher","first-page":"118","DOI":"10.1145\/3500923","volume":"65","author":"Y Moskovitch","year":"2022","unstructured":"Moskovitch, Y., Jagadish, H.: Reliability at multiple stages in a data analysis pipeline. CACM 65(11), 118\u2013128 (2022)","journal-title":"CACM"},{"key":"857_CR59","doi-asserted-by":"crossref","unstructured":"Niculescu-Mizil, A., Caruana, R.: Predicting good probabilities with supervised learning. In: ICML, pp. 625\u2013632 (2005)","DOI":"10.1145\/1102351.1102430"},{"key":"857_CR60","doi-asserted-by":"crossref","unstructured":"Pakdaman\u00a0Naeini, M., Cooper, G., Hauskrecht, M.: Obtaining well calibrated probabilities using bayesian binning. AAAI (2015)","DOI":"10.1609\/aaai.v29i1.9602"},{"key":"857_CR61","doi-asserted-by":"crossref","unstructured":"Patki, N., Wedge, R., Veeramachaneni, K.: The synthetic data vault. In: DSAA, pp. 399\u2013410 (2016)","DOI":"10.1109\/DSAA.2016.49"},{"key":"857_CR62","unstructured":"Pearce, T., Brintrup, A., Zaki, M., Neely, A.: High-quality prediction intervals for deep learning: A distribution-free, ensembled approach. In: ICML, pp. 4075\u20134084. PMLR (2018)"},{"key":"857_CR63","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/1472-6807-9-51","volume":"9","author":"B Petersen","year":"2009","unstructured":"Petersen, B., Petersen, T.N., Andersen, P., Nielsen, M., Lundegaard, C.: A generic method for assignment of reliability scores applied to solvent accessibility predictions. BMC Struct. Biol. 9, 1\u201310 (2009)","journal-title":"BMC Struct. Biol."},{"issue":"3","key":"857_CR64","first-page":"61","volume":"10","author":"J Platt","year":"1999","unstructured":"Platt, J., et al.: Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods. Adv. Large Margin Classif. 10(3), 61\u201374 (1999)","journal-title":"Adv. Large Margin Classif."},{"key":"857_CR65","doi-asserted-by":"crossref","unstructured":"Ramaswamy, S., Rastogi, R., Shim, K.: Efficient algorithms for mining outliers from large data sets. SIGMOD Rec. pp. 427-438 (2000)","DOI":"10.1145\/335191.335437"},{"key":"857_CR66","doi-asserted-by":"crossref","unstructured":"Ribeiro, M.T., Singh, S., Guestrin, C.: \" Why should i trust you?\" Explaining the predictions of any classifier. In: KDD, pp. 1135\u20131144 (2016)","DOI":"10.1145\/2939672.2939778"},{"issue":"525","key":"857_CR67","doi-asserted-by":"publisher","first-page":"223","DOI":"10.1080\/01621459.2017.1395341","volume":"114","author":"M Sadinle","year":"2019","unstructured":"Sadinle, M., Lei, J., Wasserman, L.: Least ambiguous set-valued classifiers with bounded error levels. J. Am. Stat. Assoc. 114(525), 223\u2013234 (2019)","journal-title":"J. Am. Stat. Assoc."},{"issue":"1","key":"857_CR68","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1145\/3422648.3422657","volume":"49","author":"B Salimi","year":"2020","unstructured":"Salimi, B., Howe, B., Suciu, D.: Database repair meets algorithmic fairness. ACM SIGMOD Rec. 49(1), 34\u201341 (2020)","journal-title":"ACM SIGMOD Rec."},{"key":"857_CR69","doi-asserted-by":"crossref","unstructured":"Salimi, B., Rodriguez, L., Howe, B., Suciu, D.: Interventional fairness: Causal database repair for algorithmic fairness. In: SIGMOD, pp. 793\u2013810 (2019)","DOI":"10.1145\/3299869.3319901"},{"key":"857_CR70","unstructured":"Shafer, G., Vovk, V.: A tutorial on conformal prediction. JMLR 9(3), (2008)"},{"issue":"3","key":"857_CR71","doi-asserted-by":"publisher","first-page":"379","DOI":"10.1002\/j.1538-7305.1948.tb01338.x","volume":"27","author":"CE Shannon","year":"1948","unstructured":"Shannon, C.E.: A mathematical theory of communication. Bell Syst. Tech. J. 27(3), 379\u2013423 (1948)","journal-title":"Bell Syst. Tech. J."},{"key":"857_CR72","doi-asserted-by":"crossref","unstructured":"Sharma, M., Bilgic, M.: Most-surely vs. least-surely uncertain. In: ICDM, pp. 667\u2013676. IEEE (2013)","DOI":"10.1109\/ICDM.2013.15"},{"key":"857_CR73","doi-asserted-by":"crossref","unstructured":"Sheikh, M.A., Goel, A.K., Kumar, T.: An approach for prediction of loan approval using machine learning algorithm. In: ICESC, pp. 490\u2013494. IEEE (2020)","DOI":"10.1109\/ICESC48915.2020.9155614"},{"key":"857_CR74","doi-asserted-by":"crossref","unstructured":"Sindhwani, V., Keerthi, S.S.: Large scale semi-supervised linear svms. In: SIGIR, pp. 477\u2013484 (2006)","DOI":"10.1145\/1148170.1148253"},{"key":"857_CR75","doi-asserted-by":"crossref","unstructured":"Singh, R., Vatsa, M., Ratha, N.: Trustworthy AI. In: IKDD, pp. 449\u2013453. IKDD (2021)","DOI":"10.1145\/3430984.3431966"},{"issue":"2","key":"857_CR76","first-page":"18","volume":"7","author":"N Suguna","year":"2010","unstructured":"Suguna, N., Thanushkodi, K.: An improved k-nearest neighbor classification using genetic algorithm. Int. J. Comput. Sci. Issues 7(2), 18\u201321 (2010)","journal-title":"Int. J. Comput. Sci. Issues"},{"key":"857_CR77","doi-asserted-by":"crossref","unstructured":"Sun, C., Asudeh, A., Jagadish, H., Howe, B., Stoyanovich, J.: Mithralabel: Flexible dataset nutritional labels for responsible data science. In: CIKM, pp. 2893\u20132896 (2019)","DOI":"10.1145\/3357384.3357853"},{"key":"857_CR78","doi-asserted-by":"crossref","unstructured":"Tae, K.H., Whang, S.E.: Slice tuner: A selective data acquisition framework for accurate and fair machine learning models. In: SIGMOD, pp. 1771\u20131783 (2021)","DOI":"10.1145\/3448016.3452792"},{"issue":"5","key":"857_CR79","doi-asserted-by":"publisher","first-page":"988","DOI":"10.1109\/72.788640","volume":"10","author":"VN Vapnik","year":"1999","unstructured":"Vapnik, V.N.: An overview of statistical learning theory. IEEE Trans. Neural Netw. 10(5), 988\u2013999 (1999)","journal-title":"IEEE Trans. Neural Netw."},{"issue":"10","key":"857_CR80","doi-asserted-by":"publisher","first-page":"64","DOI":"10.1145\/3448248","volume":"64","author":"JM Wing","year":"2021","unstructured":"Wing, J.M.: Trustworthy AI. CACM 64(10), 64\u201371 (2021)","journal-title":"CACM"},{"issue":"10","key":"857_CR81","doi-asserted-by":"publisher","first-page":"2311","DOI":"10.1016\/S0031-3203(01)00132-7","volume":"35","author":"Y Wu","year":"2002","unstructured":"Wu, Y., Ianakiev, K., Govindaraju, V.: Improved k-nearest neighbor classification. Pattern Recogn. 35(10), 2311\u20132318 (2002)","journal-title":"Pattern Recogn."},{"key":"857_CR82","doi-asserted-by":"crossref","unstructured":"Xu, Z., Kakde, D., Chaudhuri, A.: Automatic hyperparameter tuning method for local outlier factor, with applications to anomaly detection. In: Big Data, pp. 4201\u20134207. IEEE Computer Society (2019)","DOI":"10.1109\/BigData47090.2019.9006151"},{"key":"857_CR83","doi-asserted-by":"crossref","unstructured":"Yeh, I.C., hui Lien, C.: The comparisons of data mining techniques for the predictive accuracy of probability of default of credit card clients. Expert Systems with Applications pp. 2473\u20132480 (2009)","DOI":"10.1016\/j.eswa.2007.12.020"},{"key":"857_CR84","unstructured":"Zadrozny, B., Elkan, C.: Obtaining calibrated probability estimates from decision trees and naive bayesian classifiers. In: ICML, vol.\u00a01, pp. 609\u2013616. Citeseer (2001)"},{"key":"857_CR85","doi-asserted-by":"crossref","unstructured":"Zadrozny, B., Elkan, C.: Transforming classifier scores into accurate multiclass probability estimates. In: KDD, pp. 694\u2013699 (2002)","DOI":"10.1145\/775047.775151"},{"key":"857_CR86","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Liao, Q.V., Bellamy, R.K.E.: Effect of confidence and explanation on accuracy and trust calibration in AI-assisted decision making. In: FAccT, pp. 295\u2013305 (2020)","DOI":"10.1145\/3351095.3372852"},{"key":"857_CR87","unstructured":"Zhao, Y., Nasrullah, Z., Li, Z.: PYOD: a python toolbox for scalable outlier detection. JMLR pp. 1\u20137 (2019)"}],"container-title":["The VLDB Journal"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00778-024-00857-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00778-024-00857-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00778-024-00857-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,24]],"date-time":"2024-07-24T11:12:26Z","timestamp":1721819546000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00778-024-00857-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,30]]},"references-count":87,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2024,7]]}},"alternative-id":["857"],"URL":"https:\/\/doi.org\/10.1007\/s00778-024-00857-w","relation":{},"ISSN":["1066-8888","0949-877X"],"issn-type":[{"type":"print","value":"1066-8888"},{"type":"electronic","value":"0949-877X"}],"subject":[],"published":{"date-parts":[[2024,5,30]]},"assertion":[{"value":"30 January 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 March 2024","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 May 2024","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 May 2024","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}