{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,5]],"date-time":"2022-04-05T17:01:53Z","timestamp":1649178113249},"reference-count":36,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2012,3,1]],"date-time":"2012-03-01T00:00:00Z","timestamp":1330560000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2013,8]]},"DOI":"10.1007\/s00521-012-0897-2","type":"journal-article","created":{"date-parts":[[2012,2,28]],"date-time":"2012-02-28T22:36:42Z","timestamp":1330468602000},"page":"299-310","source":"Crossref","is-referenced-by-count":1,"title":["An adaptive class pairwise dimensionality reduction algorithm"],"prefix":"10.1007","volume":"23","author":[{"given":"Lifang","family":"He","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaowei","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhifeng","family":"Hao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2012,3,1]]},"reference":[{"key":"897_CR1","volume-title":"Statistical learning theory","author":"V Vapnik","year":"1998","unstructured":"Vapnik V (1998) Statistical learning theory. Wiley-Interscience, New York"},{"key":"897_CR2","unstructured":"Gidudu A, Ruther H (2007) Comparison of feature selection techniques for SVM classification. In: Schaepman ME, Liang S, Groot NE, Kneub\u00fchler M (eds) Proceedings of 10th international symposium on physical measurements and spectral signatures in remote sensing, vol XXXVI. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Davos, Switzerland, pp 258\u2013263"},{"key":"897_CR3","doi-asserted-by":"crossref","first-page":"2297","DOI":"10.1109\/TGRS.2009.2039484","volume":"5","author":"M Pal","year":"2010","unstructured":"Pal M, Foody GM (2010) Feature selection for classification of hyperspectral data by SVM. IEEE Trans Geosci Remote Sens 5:2297\u20132306","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"897_CR4","unstructured":"Yu L, Liu H (2003) Feature selection for high-dimensional data: a fast correlation based filter solution. In: Proceedings of the twelfth International Conference on Machine Learning (ICML)"},{"key":"897_CR5","doi-asserted-by":"crossref","unstructured":"Zhang D, Chen S, Zhou Z (2007) Constraint score: a new filter method for feature selection with pairwise constraints. Pattern Recognit 41(5):1440\u20131451","DOI":"10.1016\/j.patcog.2007.10.009"},{"key":"897_CR6","unstructured":"Pal M (2011) Fuzzy entropy based feature selection for classification of hyperspectral data. Dimensions and Directions of Geospatial Industry, pp 18\u201321"},{"key":"897_CR7","unstructured":"Saradha A, Annandurai S (2005) A hybrid feature extraction approach for face recognition systems. Int J Graph Vis Image Process 5(5):23\u201330"},{"key":"897_CR8","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1007\/978-1-84800-007-0_11","volume-title":"Machine learning for audio, image and video analysis","author":"F Camastra","year":"2008","unstructured":"Camastra F, Vinciarelli A (2008) Machine learning for audio, image and video analysis, 1st edn. Springer, Berlin, pp 305\u2013341","edition":"1"},{"key":"897_CR9","doi-asserted-by":"crossref","unstructured":"Yang B (2009) SVM-induced dimensionality reduction and classification. In: 2009 second international conference on intelligent computation technology and automation.","DOI":"10.1109\/ICICTA.2009.782"},{"key":"897_CR10","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4757-1904-8","volume-title":"Principal component analysis","author":"I Joliffe","year":"1986","unstructured":"Joliffe I (1986) Principal component analysis. Springer, Berlin"},{"key":"897_CR11","unstructured":"Balakrishnama S, Ganapathirraju A (1998) Linear discriminate analysis. Institute for Signal and Information Processing, Mississippi State University"},{"key":"897_CR12","unstructured":"Cai D, He X, Han J (2007) Isometric projection. In: Proceedings of AAAI conference on artificial intelligence"},{"key":"897_CR13","unstructured":"He X, Cai D, Yan S, Zhang H (2005) Neighborhood preserving embedding. In: Proceedings in International Conference on Computer Vision (ICCV)"},{"key":"897_CR14","unstructured":"He X, Niyogi P (2003) Locality preserving projections. In: Proceedings of conference advances in neural information processing systems"},{"key":"897_CR15","doi-asserted-by":"crossref","unstructured":"Geng X, Zhan D-C, Zhou Z-H (2005) Supervised nonlinear dimensionality reduction for visualization and classification. IEEE Trans Syst Man Cybern Part B Cybern 35(6):1098\u20131107","DOI":"10.1109\/TSMCB.2005.850151"},{"key":"897_CR16","doi-asserted-by":"crossref","unstructured":"de Ridder D, Kouropteva O, Okun O, Pietik\u00e4inen M, Duin RPW (2003) Supervised locally linear embedding. In: Proceedings of joint conference on artificial neural networks and neural information processing","DOI":"10.1007\/3-540-44989-2_40"},{"key":"897_CR17","doi-asserted-by":"crossref","unstructured":"Silva C, Ribeiro B (2008) Selecting examples in manifold reduced feature space for active learning. In: 2008 seventh international conference on machine learning and applications","DOI":"10.1109\/ICMLA.2008.86"},{"key":"897_CR18","unstructured":"Cai D, He XF, Kun Z, Han JW, Bao HJ (2007) Locality sensitive discriminant analysis. In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), Hyderabad, India, pp 141\u2013146"},{"key":"897_CR19","unstructured":"Lukui S, Jun Z, Enhai L, Pilian H (2007) Text classification based on nonlinear dimensionality reduction techniques and support vector machines. In: Third international conference on natural computation, pp 674\u2013677"},{"key":"897_CR20","doi-asserted-by":"crossref","unstructured":"Bruske J, Sommer G (1997) An algorithm for intrinsic dimensionality estimation. In: Sommer G, Daniilidis K, Pauli J (eds) Computer analysis of images and patterns. Lecture Notes in Computer Science, vol 1296. Springer, Berlin, pp 9\u201316","DOI":"10.1007\/3-540-63460-6_94"},{"key":"897_CR21","doi-asserted-by":"crossref","unstructured":"Camastra F (2003) Data dimensionality estimation methods: a survey. Pattern Recognit 36(12):2945\u20132954","DOI":"10.1016\/S0031-3203(03)00176-6"},{"key":"897_CR22","doi-asserted-by":"crossref","unstructured":"Costa J, Girotra A, Hero AO (2005) Estimating local intrinsic dimension with k-nearest neighbor graphs. IEEE workshop on Statistical Signal Processing (SSP), Bordeaux","DOI":"10.1109\/SSP.2005.1628631"},{"issue":"5500","key":"897_CR23","doi-asserted-by":"crossref","first-page":"2319","DOI":"10.1126\/science.290.5500.2319","volume":"290","author":"JB Tenenbaum","year":"2000","unstructured":"Tenenbaum JB, de Silva V, Langford JC (2000) A global geometric framework for nonlinear dimensionality reduction. Science 290(5500):2319\u20132323","journal-title":"Science"},{"issue":"10","key":"897_CR24","doi-asserted-by":"crossref","first-page":"1404","DOI":"10.1109\/TPAMI.2002.1039212","volume":"24","author":"F Camastra","year":"2002","unstructured":"Camastra F, Vinciarelli A (2002) Estimating the intrinsic dimension of data with a fractal-based method. IEEE Trans Pattern Anal Mach Intell 24(10):1404\u20131407","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"897_CR25","unstructured":"Kegl B (2002) Intrinsic dimension estimation using packing numbers. Neural Information Processing Systems, Vancouver"},{"key":"897_CR26","unstructured":"Levina E, Bickel P (2005) Maximum likelihood estimation of intrinsic dimension. Adv Neural Inf Process Syst 17:777\u2013784"},{"key":"897_CR27","doi-asserted-by":"crossref","unstructured":"Xiao R, Zhao Q, Zhang D, Shi P (2010) Data classification on multiple manifolds. In: 2010 international conference on pattern recognition, pp 3898\u20133901","DOI":"10.1109\/ICPR.2010.949"},{"key":"897_CR28","doi-asserted-by":"crossref","unstructured":"Carter KM (2010) On local intrinsic dimension estimation and its applications. IEEE Trans Signal Process 58(2):650\u2013663","DOI":"10.1109\/TSP.2009.2031722"},{"key":"897_CR29","unstructured":"Goldberg AB, Zhu X, Singh A, Xu Z, Nowak R (2009) Multi-manifold semi-supervised learning. In: Proceedings of the twelfth international conference on artificial intelligence and statistics"},{"key":"897_CR30","doi-asserted-by":"crossref","unstructured":"Wang Y, Jiang Y, Wu Y, Zhou Z-H (2010) Multi-manifold clustering. In: Proceedings of Pacific rim international conference on artificial intelligence, pp 280\u2013291","DOI":"10.1007\/978-3-642-15246-7_27"},{"key":"897_CR31","doi-asserted-by":"crossref","unstructured":"Anand A, Suganthan PN (2009) Multiclass cancer classification by support vector machines with class-wise optimized genes and probability estimates. J Theor Biol 533\u2013540","DOI":"10.1016\/j.jtbi.2009.04.013"},{"key":"897_CR32","unstructured":"Kre\u03b2el UH-G (1999) Pairwise classification and support vector machines. In: Scholkopf B, Burges CJC, Smola AJ (eds) Advances in kernel methods: support vector learning. MIT Press, Cambridge, pp 255\u2013268"},{"issue":"5500","key":"897_CR33","doi-asserted-by":"crossref","first-page":"2323","DOI":"10.1126\/science.290.5500.2323","volume":"290","author":"ST Roweis","year":"2000","unstructured":"Roweis ST, Saul LK (2000) Nonlinear dimensionality reduction by locally linear embedding. Science 290(5500):2323\u20132326","journal-title":"Science"},{"key":"897_CR34","unstructured":"Belkin M, Niyogi P (2002) Laplacian eigenmaps for dimensionality reduction and data representation. Technical Report TR-2002-01, Department of Computer Science, University of Chicago"},{"key":"897_CR35","unstructured":"Blake C, Keogh E, Merz CJ (1998) UCI repository of machine learning databases from http:\/\/archive.ics.uci.edu\/ml\/datasets.html . Department of Information and Computer Science, University of California, Irvine"},{"key":"897_CR36","unstructured":"Chang C-C, Lin C-J (2001) LIBSVM: a library for support vector machines. Software available at http:\/\/www.csie.ntu.edu.tw\/~cjlin\/libsvm"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-012-0897-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00521-012-0897-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-012-0897-2","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,6,24]],"date-time":"2019-06-24T13:59:35Z","timestamp":1561384775000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00521-012-0897-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2012,3,1]]},"references-count":36,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2013,8]]}},"alternative-id":["897"],"URL":"https:\/\/doi.org\/10.1007\/s00521-012-0897-2","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2012,3,1]]}}}