{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T18:47:48Z","timestamp":1780598868720,"version":"3.54.1"},"publisher-location":"Cham","reference-count":38,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030917012","type":"print"},{"value":"9783030917029","type":"electronic"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-91702-9_30","type":"book-chapter","created":{"date-parts":[[2021,11,27]],"date-time":"2021-11-27T20:02:46Z","timestamp":1638043366000},"page":"453-467","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Evaluating Clustering Meta-features for Classifier Recommendation"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0679-9143","authenticated-orcid":false,"given":"Lu\u00eds P. F.","family":"Garcia","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8432-4325","authenticated-orcid":false,"given":"Felipe","family":"Campelo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5859-7362","authenticated-orcid":false,"given":"Guilherme N.","family":"Ramos","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6445-3007","authenticated-orcid":false,"given":"Adriano","family":"Rivolli","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4765-6459","authenticated-orcid":false,"given":"Andr\u00e9 C. P. de L. F.","family":"de Carvalho","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,11,28]]},"reference":[{"issue":"349","key":"30_CR1","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1080\/01621459.1975.10480256","volume":"70","author":"FB Baker","year":"1975","unstructured":"Baker, F.B., Hubert, L.J.: Measuring the power of hierarchical cluster analysis. J. Am. Stat. Assoc. 70(349), 31\u201338 (1975)","journal-title":"J. Am. Stat. Assoc."},{"key":"30_CR2","doi-asserted-by":"crossref","unstructured":"Bezdek, J.C., Pal, N.R.: Some new indexes of cluster validity. IEEE Trans. Syst. Man Cybern. Part B (Cybern.) 28(3), 301\u2013315 (1998)","DOI":"10.1109\/3477.678624"},{"issue":"4","key":"30_CR3","doi-asserted-by":"publisher","first-page":"697","DOI":"10.1515\/amcs-2017-0048","volume":"27","author":"B Bilalli","year":"2017","unstructured":"Bilalli, B., Abell\u00f3, A., Aluja-Banet, T.: On the predictive power of meta-features in OpenML. Int. J. Appl. Math. Comput. Sci. 27(4), 697\u2013712 (2017)","journal-title":"Int. J. Appl. Math. Comput. Sci."},{"key":"30_CR4","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-73263-1","volume-title":"Metalearning - Applications to Data Mining. Cognitive Technologies","author":"P Brazdil","year":"2009","unstructured":"Brazdil, P., Giraud-Carrier, C., Soares, C., Vilalta, R.: Metalearning - Applications to Data Mining. Cognitive Technologies, 1st edn. Springer, Heidelberg (2009). https:\/\/doi.org\/10.1007\/978-3-540-73263-1","edition":"1"},{"issue":"1","key":"30_CR5","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman, L.: Random forests. Mach. Learn. 45(1), 5\u201332 (2001)","journal-title":"Mach. Learn."},{"key":"30_CR6","unstructured":"Breiman, L., Friedman, J.H., Olshen, R.A., Stone, C.J.: Classification and Regression Trees. Wadsworth and Brooks (1984)"},{"key":"30_CR7","doi-asserted-by":"crossref","unstructured":"Brock, G., Pihur, V., Datta, S., Datta, S.: clValid: An R package for cluster validation. J. Stat. Softw. 25(4), 1\u201322 (2008). http:\/\/www.jstatsoft.org\/v25\/i04\/","DOI":"10.18637\/jss.v025.i04"},{"issue":"1","key":"30_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1080\/03610927408827101","volume":"3","author":"T Cali\u0144ski","year":"1974","unstructured":"Cali\u0144ski, T., Harabasz, J.: A dendrite method for cluster analysis. Commun. Stat. Theory Methods 3(1), 1\u201327 (1974)","journal-title":"Commun. Stat. Theory Methods"},{"key":"30_CR9","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"457","DOI":"10.1007\/11526018_45","volume-title":"Modeling Decisions for Artificial Intelligence","author":"C Castiello","year":"2005","unstructured":"Castiello, C., Castellano, G., Fanelli, A.M.: Meta-data: characterization of input features for meta-learning. In: Torra, V., Narukawa, Y., Miyamoto, S. (eds.) MDAI 2005. LNCS (LNAI), vol. 3558, pp. 457\u2013468. Springer, Heidelberg (2005). https:\/\/doi.org\/10.1007\/11526018_45"},{"key":"30_CR10","doi-asserted-by":"crossref","unstructured":"Cristianini, N., Shawe-Taylor, J.: An Introduction to Support Vector Machines and Other Kernel-based Learning Methods. Cambridge University Press, Cambridge (2000)","DOI":"10.1017\/CBO9780511801389"},{"key":"30_CR11","doi-asserted-by":"crossref","unstructured":"Davies, D.L., Bouldin, D.W.: A cluster separation measure. IEEE Trans. Pattern Anal. Mach. Intell. PAMI-1(2), 224\u2013227 (1979)","DOI":"10.1109\/TPAMI.1979.4766909"},{"key":"30_CR12","unstructured":"Desgraupes, B.: clusterCrit Vignette (2018). https:\/\/CRAN.R-project.org\/package=clusterCrit\/vignettes\/clusterCrit.pdf"},{"key":"30_CR13","unstructured":"Dua, D., Graff, C.: UCI machine learning repository (2017). http:\/\/archive.ics.uci.edu\/ml"},{"issue":"1","key":"30_CR14","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1080\/01969727408546059","volume":"4","author":"JC Dunn","year":"1974","unstructured":"Dunn, J.C.: Well-separated clusters and optimal fuzzy partitions. J. Cybern. 4(1), 95\u2013104 (1974)","journal-title":"J. Cybern."},{"key":"30_CR15","doi-asserted-by":"crossref","unstructured":"Filchenkov, A., Pendryak, A.: Datasets meta-feature description for recommending feature selection algorithm. In: Artificial Intelligence and Natural Language and Information Extraction, Social Media and Web Search FRUCT Conference (AINL-ISMW FRUCT), vol. 7, pp. 11\u201318 (2015)","DOI":"10.1109\/AINL-ISMW-FRUCT.2015.7382962"},{"key":"30_CR16","doi-asserted-by":"crossref","unstructured":"Garcia, L.P.F., Lorena, A.C., de Souto, M.C.P., Ho, T.K.: Classifier recommendation using data complexity measures. In: 24th International Conference on Pattern Recognition (ICPR), pp. 874\u2013879 (2018)","DOI":"10.1109\/ICPR.2018.8545110"},{"key":"30_CR17","doi-asserted-by":"crossref","unstructured":"Garcia, L.P.F., Rivolli, A., Alcoba\u00e7a, E., Lorena, A.C., de Carvalho, A.C.P.L.F.: Boosting meta-learning with simulated data complexity measures. Intell. Data Anal. 24(5), 1011\u20131028 (2020)","DOI":"10.3233\/IDA-194803"},{"issue":"2\u20133","key":"30_CR18","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1023\/A:1012801612483","volume":"17","author":"M Halkidi","year":"2001","unstructured":"Halkidi, M., Batistakis, Y., Vazirgiannis, M.: On clustering validation techniques. J. Intell. Inf. Syst. 17(2\u20133), 107\u2013145 (2001)","journal-title":"J. Intell. Inf. Syst."},{"key":"30_CR19","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"547","DOI":"10.1007\/978-3-540-31880-4_38","volume-title":"Evolutionary Multi-Criterion Optimization","author":"J Handl","year":"2005","unstructured":"Handl, J., Knowles, J.: Exploiting the trade-off \u2014 the benefits of multiple objectives in data clustering. In: Coello Coello, C.A., Hern\u00e1ndez Aguirre, A., Zitzler, E. (eds.) EMO 2005. LNCS, vol. 3410, pp. 547\u2013560. Springer, Heidelberg (2005). https:\/\/doi.org\/10.1007\/978-3-540-31880-4_38"},{"key":"30_CR20","unstructured":"Haykin, S.S.: Neural Networks: A Comprehensive Foundation. Prentice Hall, Hoboken (1999)"},{"issue":"2","key":"30_CR21","doi-asserted-by":"publisher","first-page":"190","DOI":"10.1111\/j.2044-8317.1976.tb00714.x","volume":"29","author":"L Hubert","year":"1976","unstructured":"Hubert, L., Schultz, J.: Quadratic assignment as a general data analysis strategy. Br. J. Math. Stat. Psychol. 29(2), 190\u2013241 (1976)","journal-title":"Br. J. Math. Stat. Psychol."},{"key":"30_CR22","unstructured":"Mitchell, T.M.: Machine Learning. McGraw Hill Series in Computer Science. McGraw Hill, New York (1997)"},{"key":"30_CR23","unstructured":"Montgomery, D.C.: Design and Analysis of Experiments, 5th edn. Wiley, Hoboken (2000)"},{"issue":"1","key":"30_CR24","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1007\/s10994-017-5629-5","volume":"107","author":"MA Mu\u00f1oz","year":"2018","unstructured":"Mu\u00f1oz, M.A., Villanova, L., Baatar, D., Smith-Miles, K.: Instance spaces for machine learning classification. Mach. Learn. 107(1), 109\u2013147 (2018). https:\/\/doi.org\/10.1007\/s10994-017-5629-5","journal-title":"Mach. Learn."},{"key":"30_CR25","unstructured":"Pfahringer, B., Bensusan, H., Giraud-Carrier, C.G.: Meta-learning by landmarking various learning algorithms. In: 17th International Conference on Machine Learning (ICML), pp. 743\u2013750 (2000)"},{"key":"30_CR26","doi-asserted-by":"crossref","unstructured":"Pimentel, B.A., de Carvalho, A.C.P.L.F.: A new data characterization for selecting clustering algorithms using meta-learning. Inf. Sci. 477, 203\u2013219 (2019)","DOI":"10.1016\/j.ins.2018.10.043"},{"issue":"1","key":"30_CR27","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1007\/BF00116251","volume":"1","author":"JR Quinlan","year":"1986","unstructured":"Quinlan, J.R.: Induction of decision trees. Mach. Learn. 1(1), 81\u2013106 (1986)","journal-title":"Mach. Learn."},{"key":"30_CR28","unstructured":"Ray, S., Turi, R.H.: Determination of number of clusters in k-means clustering and application in colour segmentation. In: 4th International Conference on Advances in Pattern Recognition and Digital Techniques (ICAPRDT), pp. 137\u2013143 (1999)"},{"issue":"1","key":"30_CR29","doi-asserted-by":"publisher","first-page":"83","DOI":"10.1007\/s10044-012-0280-z","volume":"17","author":"M Reif","year":"2014","unstructured":"Reif, M., Shafait, F., Goldstein, M., Breuel, T., Dengel, A.: Automatic classifier selection for non-experts. Pattern Anal. Appl. 17(1), 83\u201396 (2014)","journal-title":"Pattern Anal. Appl."},{"key":"30_CR30","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1016\/S0065-2458(08)60520-3","volume":"15","author":"JR Rice","year":"1976","unstructured":"Rice, J.R.: The algorithm selection problem. Adv. Comput. 15, 65\u2013118 (1976)","journal-title":"Adv. Comput."},{"key":"30_CR31","unstructured":"Rivolli, A., Garcia, L.P.F., Soares, C., Vanschoren, J., de Carvalho, A.C.P.L.F.: Characterizing classification datasets: a study of meta-features for meta-learning. CoRR abs\/1808.10406, 1\u201349 (2019)"},{"key":"30_CR32","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1016\/0377-0427(87)90125-7","volume":"20","author":"PJ Rousseeuw","year":"1987","unstructured":"Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. J. Comput. Appl. Math. 20, 53\u201365 (1987)","journal-title":"J. Comput. Appl. Math."},{"key":"30_CR33","volume-title":"Akaike Information Criterion Statistics","author":"Y Sakamoto","year":"1986","unstructured":"Sakamoto, Y., Ishiguro, M., Kitagawa, G.: Akaike Information Criterion Statistics. Springer, Netherlands (1986)"},{"issue":"1","key":"30_CR34","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1456650.1456656","volume":"41","author":"KA Smith-Miles","year":"2008","unstructured":"Smith-Miles, K.A.: Cross-disciplinary perspectives on meta-learning for algorithm selection. ACM Comput. Surv. 41(1), 1\u201325 (2008)","journal-title":"ACM Comput. Surv."},{"issue":"3","key":"30_CR35","doi-asserted-by":"publisher","first-page":"185","DOI":"10.2174\/1389200219666180820112457","volume":"20","author":"N Stephenson","year":"2019","unstructured":"Stephenson, N., et al.: Survey of machine learning techniques in drug discovery. Curr. Drug metab. 20(3), 185\u2013193 (2019)","journal-title":"Curr. Drug metab."},{"key":"30_CR36","unstructured":"Van Rijn, J.N., et al.: OpenML: a collaborative science platform. In: European Conference on Machine Learning and Knowledge Discovery in Databases (ECML\/PKDD), pp. 645\u2013649 (2013)"},{"issue":"2","key":"30_CR37","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1504\/IJDMB.2016.074682","volume":"14","author":"M Vukicevic","year":"2016","unstructured":"Vukicevic, M., Radovanovic, S., Delibasic, B., Suknovic, M.: Extending meta-learning framework for clustering gene expression data with component-based algorithm design and internal evaluation measures. Int. J. Data Min. Bioinform. (IJDMB) 14(2), 101\u2013119 (2016)","journal-title":"Int. J. Data Min. Bioinform. (IJDMB)"},{"issue":"8","key":"30_CR38","doi-asserted-by":"publisher","first-page":"841","DOI":"10.1109\/34.85677","volume":"13","author":"XL Xie","year":"1991","unstructured":"Xie, X.L., Beni, G.: A validity measure for fuzzy clustering. IEEE Trans. Pattern Anal. Mach. Intell. 13(8), 841\u2013847 (1991)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."}],"container-title":["Lecture Notes in Computer Science","Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-91702-9_30","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,7]],"date-time":"2024-03-07T12:06:23Z","timestamp":1709813183000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-91702-9_30"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030917012","9783030917029"],"references-count":38,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-91702-9_30","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"28 November 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"BRACIS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Brazilian Conference on Intelligent Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 November 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3 December 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"bracis2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/c4ai.inova.usp.br\/bracis\/","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":"JEMS","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"192","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":"77","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":"40% - 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","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":"3.1","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":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Due to COVID-19, the conference was held as an online event.","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)"}}]}}