乐胖代购免代理版

{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,6,25]],"date-time":"2024-06-25T08:39:52Z","timestamp":1719304792258},"reference-count":37,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2016,8,3]],"date-time":"2016-08-03T00:00:00Z","timestamp":1470182400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Adv Data Anal Classif"],"published-print":{"date-parts":[[2016,12]]},"DOI":"10.1007\/s11634-016-0264-8","type":"journal-article","created":{"date-parts":[[2016,8,3]],"date-time":"2016-08-03T05:07:48Z","timestamp":1470200868000},"page":"563-583","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["An effective strategy for initializing the EM algorithm in finite mixture models"],"prefix":"10.1007","volume":"10","author":[{"given":"Semhar","family":"Michael","sequence":"first","affiliation":[]},{"given":"Volodymyr","family":"Melnykov","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2016,8,3]]},"reference":[{"key":"264_CR1","doi-asserted-by":"crossref","first-page":"715","DOI":"10.1093\/biomet\/83.4.715","volume":"83","author":"A Azzalini","year":"1996","unstructured":"Azzalini A, Valle DA (1996) The multivariate skew-normal distribution. Biometrika 83:715\u2013726","journal-title":"Biometrika"},{"key":"264_CR2","doi-asserted-by":"crossref","first-page":"332","DOI":"10.1198\/jcgs.2010.08111","volume":"19","author":"J-P Baudry","year":"2010","unstructured":"Baudry J-P, Raftery A, Celeux G, Lo K, Gottardo R (2010) Combining mixture components for clustering. J Comput Graph Stat 19:332\u2013353","journal-title":"J Comput Graph Stat"},{"key":"264_CR3","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1023\/B:STCO.0000035306.77434.31","volume":"14","author":"C Biernacki","year":"2004","unstructured":"Biernacki C (2004) Initializing EM using the properties of its trajectories in Gaussian mixtures. Stat Comput 14:267\u2013279","journal-title":"Stat Comput"},{"key":"264_CR4","doi-asserted-by":"crossref","first-page":"561","DOI":"10.1016\/S0167-9473(02)00163-9","volume":"413","author":"C Biernacki","year":"2003","unstructured":"Biernacki C, Celeux G, Govaert G (2003) Choosing starting values for the EM algorithm for getting the highest likelihood in multivariate Gaussian mixture models. Comput Stat Data Anal 413:561\u2013575","journal-title":"Comput Stat Data Anal"},{"key":"264_CR5","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.csda.2012.12.008","volume":"71","author":"C Bouveyron","year":"2013","unstructured":"Bouveyron C, Brunet C (2013) Model-based clustering of high-dimensional data: a review. Comput Stat Data Anal 71:52\u201378","journal-title":"Comput Stat Data Anal"},{"key":"264_CR6","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1071\/ZO9740417","volume":"22","author":"NA Campbell","year":"1974","unstructured":"Campbell NA, Mahon RJ (1974) A multivariate study of variation in two species of rock crab of genus Leptograsus. Austr J Zool 22:417\u2013425","journal-title":"Austr J Zool"},{"key":"264_CR7","unstructured":"Celebi ME, Kingravi HA, Vela PA (2012) A comparative study of efficient initialization methods for the $$k$$ k -means clustering algorithm. Comput Res Reposit. arXiv:1209.1960"},{"key":"264_CR8","first-page":"73","volume":"2","author":"G Celeux","year":"1985","unstructured":"Celeux G, Diebolt J (1985) The SEM algorithm: a probabilistic teacher algorithm derived from the EM algorithm for the mixture problem. Comput Stat 2:73\u201382","journal-title":"Comput Stat"},{"key":"264_CR9","unstructured":"Chen WC, Maitra R (2015) EMCluster: EM Algorithm for Model-Based Clustering of Finite Mixture Gaussian Distribution, R Package. http:\/\/cran.r-project.org\/package=EMCluster"},{"key":"264_CR10","doi-asserted-by":"crossref","first-page":"323","DOI":"10.1023\/B:STCO.0000039481.32211.5a","volume":"14","author":"J Dias","year":"2004","unstructured":"Dias J, Wedel M (2004) An empirical comparison of EM, SEM and MCMC performance for problematic Gaussian mixture likelihoods. Stat Comput 14:323\u2013332","journal-title":"Stat Comput"},{"key":"264_CR11","first-page":"768","volume":"21","author":"E Forgy","year":"1965","unstructured":"Forgy E (1965) Cluster analysis of multivariate data: efficiency vs. interpretability of classifications. Biometrics 21:768\u2013780","journal-title":"Biometrics"},{"key":"264_CR12","doi-asserted-by":"crossref","first-page":"270","DOI":"10.1137\/S1064827596311451","volume":"20","author":"C Fraley","year":"1998","unstructured":"Fraley C (1998) Algorithms for model-based gaussian hierarchical clustering. SIAM J Sci Comput 20:270\u2013281","journal-title":"SIAM J Sci Comput"},{"key":"264_CR13","doi-asserted-by":"crossref","first-page":"578","DOI":"10.1093\/comjnl\/41.8.578","volume":"41","author":"C Fraley","year":"1998","unstructured":"Fraley C, Raftery AE (1998) How many clusters? Which cluster method? Answers via model-based cluster analysis. Comput J 41:578\u2013588","journal-title":"Comput J"},{"key":"264_CR14","doi-asserted-by":"crossref","first-page":"611","DOI":"10.1198\/016214502760047131","volume":"97","author":"C Fraley","year":"2002","unstructured":"Fraley C, Raftery AE (2002) Model-based clustering, discriminant analysis, and density estimation. J Am Stat Assoc 97:611\u2013631","journal-title":"J Am Stat Assoc"},{"key":"264_CR15","doi-asserted-by":"crossref","unstructured":"Fraley C, Raftery AE (2006) MCLUST version 3 for R: normal mixture modeling and model-based clustering. Tech. Rep. 504. University of Washington, Department of Statistics, Seattle","DOI":"10.21236\/ADA456562"},{"key":"264_CR16","doi-asserted-by":"crossref","unstructured":"Hennig C (2010) Methods for merging Gaussian mixture components. Adv Data Anal Class 4(1):3\u201334","DOI":"10.1007\/s11634-010-0058-3"},{"key":"264_CR17","doi-asserted-by":"crossref","unstructured":"Hershey JR, Olsen PA (2007) Approximating the kullback leibler divergence between gaussian mixture models. In: IEEE International Conference on Acoustics, Speech and Signal Processing-ICASSP\u201907, pp IV-317\u2013IV-320","DOI":"10.1109\/ICASSP.2007.366913"},{"key":"264_CR18","doi-asserted-by":"crossref","first-page":"382","DOI":"10.1214\/ss\/1009212519","volume":"14","author":"JA Hoeting","year":"1999","unstructured":"Hoeting JA, Madigan DM, Raftery AE, Volinsky CT (1999) Bayesian model averaging: a tutorial. Stat Sci 14:382\u2013417 (with discussion)","journal-title":"Stat Sci"},{"key":"264_CR19","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1007\/BF01908075","volume":"2","author":"L Hubert","year":"1985","unstructured":"Hubert L, Arabie P (1985) Comparing partitions. J Classif 2:193\u2013218","journal-title":"J Classif"},{"key":"264_CR20","doi-asserted-by":"crossref","DOI":"10.1002\/9780470316801","volume-title":"Finding Groups in Data","author":"L Kaufman","year":"1990","unstructured":"Kaufman L, Rousseuw PJ (1990) Finding Groups in Data. Wiley, New York"},{"key":"264_CR21","doi-asserted-by":"publisher","unstructured":"Lebret R, Iovleff S, Langrognet F, Biernacki C, Celeux G, Govaert G (2015) Rmixmod: the R package of the model-based unsupervised, supervised, and semi-supervised classification mixmod library. J Stat Softw 67(6). doi: 10.18637\/jss.v067.i06","DOI":"10.18637\/jss.v067.i06"},{"key":"264_CR22","first-page":"281","volume":"1","author":"J MacQueen","year":"1967","unstructured":"MacQueen J (1967) Some methods for classification and analysis of multivariate observations. Proc Fifth Berkeley Symp 1:281\u2013297","journal-title":"Proc Fifth Berkeley Symp"},{"key":"264_CR23","doi-asserted-by":"crossref","first-page":"1535","DOI":"10.1080\/01621459.1994.10476894","volume":"89","author":"D Madigan","year":"1994","unstructured":"Madigan D, Raftery AE (1994) Model selection and accounting for model uncertainty in graphical models using Occams window. J Am Stat Assoc 89:1535\u20131546","journal-title":"J Am Stat Assoc"},{"key":"264_CR24","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1109\/TCBB.2007.70244","volume":"6","author":"R Maitra","year":"2009","unstructured":"Maitra R (2009) Initializing partition-optimization algorithms. IEEE\/ACM Trans Comput Biol Bioinf 6:144\u2013157","journal-title":"IEEE\/ACM Trans Comput Biol Bioinf"},{"key":"264_CR25","doi-asserted-by":"crossref","first-page":"354","DOI":"10.1198\/jcgs.2009.08054","volume":"19","author":"R Maitra","year":"2010","unstructured":"Maitra R, Melnykov V (2010) Simulating data to study performance of finite mixture modeling and clustering algorithms. J Comput Graph Stat 19:354\u2013376","journal-title":"J Comput Graph Stat"},{"key":"264_CR26","doi-asserted-by":"crossref","DOI":"10.1002\/0471721182","volume-title":"Finite Mixture Models","author":"G McLachlan","year":"2000","unstructured":"McLachlan G, Peel D (2000) Finite Mixture Models. Wiley, New York"},{"key":"264_CR27","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1002\/wics.1248","volume":"5","author":"V Melnykov","year":"2013","unstructured":"Melnykov V (2013) Challenges in model-based clustering. WIREs Comput Stat 5:135\u2013148","journal-title":"WIREs Comput Stat"},{"key":"264_CR28","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1080\/10618600.2014.978007","volume":"25","author":"V Melnykov","year":"2016","unstructured":"Melnykov V (2016) Merging mixture components for clustering through pairwise overlap. J Comput Graph Stat 25:66\u201390","journal-title":"J Comput Graph Stat"},{"key":"264_CR29","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v051.i12","volume":"51","author":"V Melnykov","year":"2012","unstructured":"Melnykov V, Chen W-C, Maitra R (2012) MixSim: R package for simulating datasets with pre-specified clustering complexity. J Stat Softw 51:1\u201325","journal-title":"J Stat Softw"},{"key":"264_CR30","doi-asserted-by":"crossref","first-page":"1381","DOI":"10.1016\/j.csda.2011.11.002","volume":"56","author":"V Melnykov","year":"2012","unstructured":"Melnykov V, Melnykov I (2012) Initializing the EM algorithm in Gaussian mixture models with an unknown number of components. Comput Stat Data Anal 56:1381\u20131395","journal-title":"Comput Stat Data Anal"},{"key":"264_CR31","doi-asserted-by":"crossref","unstructured":"Melnykov V, Melnykov I, Michael S (2015a) Semi-supervised model-based clustering with positive and negative constraints. In: Advances in data analysis and classification, pp 1\u201323","DOI":"10.1007\/s11634-015-0200-3"},{"key":"264_CR32","doi-asserted-by":"crossref","unstructured":"Melnykov V, Michael S, Melnykov I (2015b) Recent developments in model-based clustering with applications. In: Celebi ME (ed) Partitional clustering algorithms, vol 1. Springer, Berlin, pp 1\u201339","DOI":"10.1007\/978-3-319-09259-1_1"},{"key":"264_CR33","doi-asserted-by":"crossref","unstructured":"Prates M, Lachos V, Cabral C (2013) Mixsmsn: fitting finite mixture of scale mixture of skew-normal distributions. J Stat Softw 54(12):1\u201320","DOI":"10.18637\/jss.v054.i12"},{"key":"264_CR34","first-page":"201","volume":"17","author":"P Sneath","year":"1957","unstructured":"Sneath P (1957) The application of computers to taxonomy. J Gener Microbiol 17:201\u2013226","journal-title":"J Gener Microbiol"},{"key":"264_CR35","first-page":"1","volume":"5","author":"T Sorensen","year":"1948","unstructured":"Sorensen T (1948) A method of establishing groups of equal amplitude in plant sociology based on similarity of species content and its application to analyses of the vegetation on Danish commons. Biologiske Skrifter 5:1\u201334","journal-title":"Biologiske Skrifter"},{"key":"264_CR36","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1002\/wics.1204","volume":"4","author":"D Stahl","year":"2012","unstructured":"Stahl D, Sallis H (2012) Model-based cluster analysis. Wiley Interdiscipl Rev Comput Stat 4:341\u2013358","journal-title":"Wiley Interdiscipl Rev Comput Stat"},{"key":"264_CR37","doi-asserted-by":"crossref","first-page":"236","DOI":"10.1080\/01621459.1963.10500845","volume":"58","author":"JH Ward","year":"1963","unstructured":"Ward JH (1963) Hierarchical grouping to optimize an objective function. J Am Stat Assoc 58:236\u2013244","journal-title":"J Am Stat Assoc"}],"container-title":["Advances in Data Analysis and Classification"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11634-016-0264-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11634-016-0264-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11634-016-0264-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,9,11]],"date-time":"2019-09-11T23:17:14Z","timestamp":1568243834000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11634-016-0264-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,8,3]]},"references-count":37,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2016,12]]}},"alternative-id":["264"],"URL":"https:\/\/doi.org\/10.1007\/s11634-016-0264-8","relation":{},"ISSN":["1862-5347","1862-5355"],"issn-type":[{"value":"1862-5347","type":"print"},{"value":"1862-5355","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,8,3]]}}}