{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,9]],"date-time":"2024-09-09T18:08:35Z","timestamp":1725905315574},"publisher-location":"Cham","reference-count":22,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319633114"},{"type":"electronic","value":"9783319633121"}],"license":[{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017]]},"DOI":"10.1007\/978-3-319-63312-1_11","type":"book-chapter","created":{"date-parts":[[2017,7,19]],"date-time":"2017-07-19T11:43:13Z","timestamp":1500464593000},"page":"125-131","source":"Crossref","is-referenced-by-count":0,"title":["Feature Selection Based on Density Peak Clustering Using Information Distance Measure"],"prefix":"10.1007","author":[{"given":"Jie","family":"Cai","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shilong","family":"Chao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sheng","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shulin","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiawei","family":"Luo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2017,7,20]]},"reference":[{"issue":"1","key":"11_CR1","first-page":"245","volume":"97","author":"LB Avrim","year":"1997","unstructured":"Avrim, L.B., Langley, P.: Selection of relevant features and examples in machine learning. Artif. Intell. 97(1), 245\u2013271 (1997)","journal-title":"Artif. Intell."},{"key":"11_CR2","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4615-5689-3","volume-title":"Feature Selection for Knowledge Discovery and Data Mining","author":"H Liu","year":"1998","unstructured":"Liu, H., Motoda, H.: Feature Selection for Knowledge Discovery and Data Mining. Kluwer Academic Publishers, Boston (1998)"},{"issue":"8","key":"11_CR3","doi-asserted-by":"crossref","first-page":"1226","DOI":"10.1109\/TPAMI.2005.159","volume":"27","author":"H Peng","year":"2005","unstructured":"Peng, H., Long, F., Ding, C.: Feature selection based on mutual information: criteria of max-dependency, max-relevance, and min-redundancy. IEEE Trans. Pattern Anal. Mach. Intell. 27(8), 1226\u20131238 (2005)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"11_CR4","first-page":"1531","volume":"5","author":"F Fleuret","year":"2004","unstructured":"Fleuret, F.: Fast binary feature selection with conditional mutual information. J. Mach. Learn. Res. 5, 1531\u20131555 (2004)","journal-title":"J. Mach. Learn. Res."},{"key":"11_CR5","unstructured":"Hall, M.A.: Correlation-based feature selection for discrete and numeric class machine learning. In: Proceedings of the 7th International Conference on Machine Learning, pp. 359\u2013366 (2000)"},{"key":"11_CR6","first-page":"1205","volume":"5","author":"L Yu","year":"2004","unstructured":"Yu, L., Liu, H.: Efficient feature selection via analysis of relevance and redundancy. J. Mach. Learn. Res. 5, 1205\u20131224 (2004)","journal-title":"J. Mach. Learn. Res."},{"issue":"3","key":"11_CR7","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1109\/34.990133","volume":"24","author":"P Mitra","year":"2002","unstructured":"Mitra, P., Murthy, C.: Unsupervised feature selection using similarity. IEEE Trans. Pattern Anal. Mach. Intell. 24(3), 301\u2013312 (2002)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"11_CR8","doi-asserted-by":"crossref","unstructured":"Ienco, D., Meo, R.: Exploration and reduction of the feature space by hierarchical clustering. In: Proceedings of the 2008 SIAM Conference on Data Mining, Atlanta, Georgia, USA, pp. 577\u2013587 (2008)","DOI":"10.1137\/1.9781611972788.53"},{"key":"11_CR9","doi-asserted-by":"crossref","first-page":"713","DOI":"10.1198\/jasa.2010.tm09415","volume":"105","author":"D Witten","year":"2010","unstructured":"Witten, D., Tibshirni, R.: A framework for feature selection in clustering. J. Am. Stat. Associ. 105, 713\u2013726 (2010)","journal-title":"J. Am. Stat. Associ."},{"key":"11_CR10","doi-asserted-by":"crossref","unstructured":"Liu, H., Wu, X., Zhang, S.: Feature selection using hierarchical feature clustering. In: Proceedings of the 20th ACM International Conference on Information and Knowledge Management, Glasgow, United Kingdom, pp. 979\u2013984 (2011)","DOI":"10.1145\/2063576.2063716"},{"issue":"2","key":"11_CR11","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.procs.2013.05.011","volume":"17","author":"X Zhao","year":"2013","unstructured":"Zhao, X., Deng, W., Shi, Y.: Feature selection with attributes clustering by maximal information coefficient. Procedia Comput. Sci. 17(2), 70\u201379 (2013)","journal-title":"Procedia Comput. Sci."},{"issue":"1","key":"11_CR12","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1016\/j.patrec.2013.12.008","volume":"40","author":"S Bandyopadhyay","year":"2014","unstructured":"Bandyopadhyay, S., Bhadra, T., Mitra, P., et al.: Integration of dense subgraph finding with feature clustering for unsupervised feature selection. Pattern Recogn. Lett. 40(1), 104\u2013112 (2014)","journal-title":"Pattern Recogn. Lett."},{"issue":"2","key":"11_CR13","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1109\/TCBB.2005.17","volume":"2","author":"WH Au","year":"2005","unstructured":"Au, W.H., Chan, K.C., Wong, A.K., Wang, Y.: Attribute clustering for grouping, selection, and classification of gene expression data. IEEE\/ACM Trans. Comput. Biol. Bioinf. 2(2), 83\u2013101 (2005)","journal-title":"IEEE\/ACM Trans. Comput. Biol. Bioinf."},{"issue":"1","key":"11_CR14","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TKDE.2011.181","volume":"25","author":"Q Song","year":"2013","unstructured":"Song, Q., Ni, J., Wang, G.: A fast clustering-based feature subset selection algorithm for high-dimensional data. IEEE Trans. Knowl. Data Eng. 25(1), 1\u201314 (2013)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"11_CR15","doi-asserted-by":"crossref","unstructured":"Liu, Q., Zhang, J., Xiao J., Zhu, H., Zhao, Q.: A supervised feature selection algorithm through minimum spanning tree clustering. In: IEEE 26th International Conference on Tools with Artificial Intelligence, pp. 264\u2013271 (2014)","DOI":"10.1109\/ICTAI.2014.47"},{"issue":"5","key":"11_CR16","doi-asserted-by":"crossref","first-page":"873","DOI":"10.1016\/j.jmva.2006.11.013","volume":"98","author":"M Meila","year":"2007","unstructured":"Meila, M.: Comparing clusterings - an information based distance. J. Multivar. Anal. 98(5), 873\u2013895 (2007)","journal-title":"J. Multivar. Anal."},{"issue":"10","key":"11_CR17","first-page":"2837","volume":"11","author":"NX Vinh","year":"2010","unstructured":"Vinh, N.X., Epps, J., Bailey, J.: Information theoretic measures for clusterings comparison: variants, properties, normalization and correction for chance. J. Mach. Learn. Res. 11(10), 2837\u20132854 (2010)","journal-title":"J. Mach. Learn. Res."},{"issue":"6191","key":"11_CR18","doi-asserted-by":"crossref","first-page":"1492","DOI":"10.1126\/science.1242072","volume":"344","author":"A Rodriguez","year":"2014","unstructured":"Rodriguez, A., Laio, A.: Clustering by fast search and find of density peaks. Science 344(6191), 1492\u20131496 (2014)","journal-title":"Science"},{"key":"11_CR19","unstructured":"Fayyad, U.M., Irani, K.B.: Multi-interval discretization of continuous-valued attributes for classification learning. In: Proceedings of the IJCAI, pp. 1022\u20131029 (1993)"},{"key":"11_CR20","unstructured":"Yang, H.H., Moody, J.E.: Data visualization and feature selection: new algorithms for nongaussian data. In: Proceedings of the NIPS, pp. 687\u2013693 (1999)"},{"key":"11_CR21","first-page":"171","volume":"14","author":"I Kononenko","year":"1994","unstructured":"Kononenko, I.: Estimating attributes: analysis and extensions of RELIEF. Mach. Learn. 14, 171\u2013182 (1994)","journal-title":"Mach. Learn."},{"issue":"6","key":"11_CR22","doi-asserted-by":"crossref","first-page":"2068","DOI":"10.1016\/j.patcog.2009.12.013","volume":"43","author":"JM Sotoca","year":"2010","unstructured":"Sotoca, J.M., Pla, F.: Supervised feature selection by clustering using conditional mutual information-based distances. Pattern Recogn. 43(6), 2068\u20132081 (2010)","journal-title":"Pattern Recogn."}],"container-title":["Lecture Notes in Computer Science","Intelligent Computing Theories and Application"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-63312-1_11","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2017,7,19]],"date-time":"2017-07-19T11:47:52Z","timestamp":1500464872000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-63312-1_11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"ISBN":["9783319633114","9783319633121"],"references-count":22,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-63312-1_11","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2017]]}}}