{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T11:57:58Z","timestamp":1742990278379,"version":"3.40.3"},"publisher-location":"Cham","reference-count":18,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031236174"},{"type":"electronic","value":"9783031236181"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-3-031-23618-1_18","type":"book-chapter","created":{"date-parts":[[2023,1,30]],"date-time":"2023-01-30T07:05:49Z","timestamp":1675062349000},"page":"261-268","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Bitpaths: Compressing Datasets Without Decreasing Predictive Performance"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4479-3781","authenticated-orcid":false,"given":"Loren","family":"Nuyts","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1549-749X","authenticated-orcid":false,"given":"Laurens","family":"Devos","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9560-3872","authenticated-orcid":false,"given":"Wannes","family":"Meert","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3748-9263","authenticated-orcid":false,"given":"Jesse","family":"Davis","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,1,31]]},"reference":[{"key":"18_CR1","doi-asserted-by":"crossref","unstructured":"Breiman, L.: Random forests. Mach. Learn. 45, 5\u201332 (2001)","DOI":"10.1023\/A:1010933404324"},{"issue":"11","key":"18_CR2","doi-asserted-by":"publisher","first-page":"2783","DOI":"10.1890\/07-0539.1","volume":"88","author":"DR Cutler","year":"2007","unstructured":"Cutler, D.R., et al.: Random forests for classification in ecology. Ecology 88(11), 2783\u20132792 (2007)","journal-title":"Ecology"},{"key":"18_CR3","unstructured":"Demsar, J.: Statistical comparisons of classifiers over multiple data sets. J. Mach. Learn. Res. 7, 1\u201330 (2006)"},{"key":"18_CR4","unstructured":"Devos, L., Meert, W., Davis, J.: Adversarial example detection in deployed tree ensembles (2022)"},{"issue":"293","key":"18_CR5","doi-asserted-by":"publisher","first-page":"52","DOI":"10.1080\/01621459.1961.10482090","volume":"56","author":"OJ Dunn","year":"1961","unstructured":"Dunn, O.J.: Multiple comparisons among means. J. Am. Stat. Assoc. 56(293), 52\u201364 (1961)","journal-title":"J. Am. Stat. Assoc."},{"issue":"200","key":"18_CR6","doi-asserted-by":"publisher","first-page":"675","DOI":"10.1080\/01621459.1937.10503522","volume":"32","author":"M Friedman","year":"1937","unstructured":"Friedman, M.: The use of ranks to avoid the assumption of normality implicit in the analysis of variance. J. Am. Stat. Assoc. 32(200), 675\u2013701 (1937)","journal-title":"J. Am. Stat. Assoc."},{"issue":"1","key":"18_CR7","doi-asserted-by":"publisher","first-page":"86","DOI":"10.1214\/aoms\/1177731944","volume":"11","author":"M Friedman","year":"1940","unstructured":"Friedman, M.: A comparison of alternative tests of significance for the problem of $$m$$ rankings. Ann. Math. Stat. 11(1), 86\u201392 (1940)","journal-title":"Ann. Math. Stat."},{"key":"18_CR8","doi-asserted-by":"crossref","unstructured":"Gislason, P.O., Benediktsson, J.A., Sveinsson, J.R.: Random forests for land cover classification. Pattern Recogn. Lett. 27(4), 294\u2013300 (2006). Pattern Recognition in Remote Sensing (PRRS 2004)","DOI":"10.1016\/j.patrec.2005.08.011"},{"key":"18_CR9","doi-asserted-by":"publisher","first-page":"890","DOI":"10.1016\/j.conbuildmat.2018.09.017","volume":"189","author":"H Gong","year":"2018","unstructured":"Gong, H., Sun, Y., Shu, X., Huang, B.: Use of random forests regression for predicting IRI of asphalt pavements. Constr. Build. Mater. 189, 890\u2013897 (2018)","journal-title":"Constr. Build. Mater."},{"key":"18_CR10","doi-asserted-by":"crossref","unstructured":"Iman, R.L., Davenport, J.M.: Approximations of the critical region of the Friedman statistic. Commun. Stat., 571\u2013595 (1980)","DOI":"10.1080\/03610928008827904"},{"issue":"1","key":"18_CR11","doi-asserted-by":"publisher","first-page":"117","DOI":"10.1109\/TPAMI.2010.57","volume":"33","author":"H J\u00e9gou","year":"2011","unstructured":"J\u00e9gou, H., Douze, M., Schmid, C.: Product quantization for nearest neighbor search. IEEE Trans. Pattern Anal. Mach. Intell. 33(1), 117\u2013128 (2011)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"18_CR12","doi-asserted-by":"crossref","unstructured":"Makhalova, T., Kuznetsov, S.O., Napoli, A.: Numerical pattern mining through compression, pp. 112\u2013121 (2019)","DOI":"10.1109\/DCC.2019.00019"},{"key":"18_CR13","doi-asserted-by":"crossref","unstructured":"Montillo, A., Ling, H.: Age regression from faces using random forests. In: 16th IEEE International Conference on Image Processing, pp. 2465\u20132468 (2009)","DOI":"10.1109\/ICIP.2009.5414103"},{"key":"18_CR14","unstructured":"Nemenyi, P.B.: Distribution-free multiple comparisons. Ph.D. thesis, Princeton University (1963)"},{"key":"18_CR15","doi-asserted-by":"crossref","unstructured":"Park, J., Park, H., Choi, Y.J.: Data compression and prediction using machine learning for industrial IoT. In: 2018 International Conference on Information Networking (ICOIN), pp. 818\u2013820 (2018)","DOI":"10.1109\/ICOIN.2018.8343232"},{"key":"18_CR16","doi-asserted-by":"crossref","unstructured":"Pliakos, K., Vens, C.: Feature induction based on extremely randomized tree paths. In: Online Proceedings, pp. 3\u201318 (2016)","DOI":"10.1007\/978-3-319-61461-8_1"},{"key":"18_CR17","doi-asserted-by":"crossref","unstructured":"Sculley, D., Brodley, C.: Compression and machine learning: a new perspective on feature space vectors. In: Data Compression Conference, pp. 332\u2013341 (2006)","DOI":"10.1109\/DCC.2006.13"},{"key":"18_CR18","doi-asserted-by":"crossref","unstructured":"Vreeken, J., Van Leeuwen, M., Siebes, A.: KRIMP: mining itemsets that compress. Data Mining Knowl. Discov. 23(1), 169\u2013214 (2011)","DOI":"10.1007\/s10618-010-0202-x"}],"container-title":["Communications in Computer and Information Science","Machine Learning and Principles and Practice of Knowledge Discovery in Databases"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-23618-1_18","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,13]],"date-time":"2024-10-13T06:47:19Z","timestamp":1728802039000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-23618-1_18"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031236174","9783031236181"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-23618-1_18","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"31 January 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECML PKDD","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Joint European Conference on Machine Learning and Knowledge Discovery in Databases","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Grenoble","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"France","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 September 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 September 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ecml2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/2022.ecmlpkdd.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"1060","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"236","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"22% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3-4","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3-4","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"17 demo track papers have been accepted from 28 submissions","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}