메뉴 건너뛰기




Volumn 93, Issue , 2012, Pages 115-125

Graph embedding based feature selection

Author keywords

Feature selection; Gene selection; Graph embedding; Manifold learning; Recursive feature elimination

Indexed keywords

DATA SETS; FEATURE SUBSET; GENE SELECTION; GRAPH EMBEDDINGS; INTRINSIC CHARACTERISTICS; LEARNING PERFORMANCE; LINEAR DISCRIMINANT ANALYSIS; MANIFOLD LEARNING; MARGINAL FISHER ANALYSIS; MICROARRAY DATA ANALYSIS; NEGATIVE INFLUENCE; REAL DATA SETS; RECURSIVE FEATURE ELIMINATION; REDUNDANT FEATURES; SELECTION TECHNIQUES;

EID: 84862179349     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2012.03.016     Document Type: Article
Times cited : (13)

References (24)
  • 1
    • 44649111202 scopus 로고    scopus 로고
    • Locality sensitive semi-supervised feature selection
    • Zhao J., Lu K., He X. Locality sensitive semi-supervised feature selection. Neurocomputing 2008, 71:1842-1849.
    • (2008) Neurocomputing , vol.71 , pp. 1842-1849
    • Zhao, J.1    Lu, K.2    He, X.3
  • 3
    • 77955319589 scopus 로고    scopus 로고
    • Kernel based gene expression pattern discovery and its application on cancer classification
    • Cai R., Hao Z., Wen W., Huang H. Kernel based gene expression pattern discovery and its application on cancer classification. Neurocomputing 2010, 73:2562-2570.
    • (2010) Neurocomputing , vol.73 , pp. 2562-2570
    • Cai, R.1    Hao, Z.2    Wen, W.3    Huang, H.4
  • 5
    • 78650724578 scopus 로고    scopus 로고
    • Unsupervised feature extraction via kernel subspace techniques
    • Teixeira A.R., Tomé A.M., Lang E.W. Unsupervised feature extraction via kernel subspace techniques. Neurocomputing 2011, 74:820-830.
    • (2011) Neurocomputing , vol.74 , pp. 820-830
    • Teixeira, A.R.1    Tomé, A.M.2    Lang, E.W.3
  • 7
    • 79954420816 scopus 로고    scopus 로고
    • Sparse kernel density estimations and its application in variable selection based on quadratic Renyi entropy
    • Han M., Liang Z.P., Li D.C. Sparse kernel density estimations and its application in variable selection based on quadratic Renyi entropy. Neurocomputing 2011, 74:1664-1672.
    • (2011) Neurocomputing , vol.74 , pp. 1664-1672
    • Han, M.1    Liang, Z.P.2    Li, D.C.3
  • 8
    • 77952545392 scopus 로고    scopus 로고
    • Feature evaluation and selection based on neighborhood soft margin
    • Hu Q.H., Che X.J., Zhang Lei L. Feature evaluation and selection based on neighborhood soft margin. Neurocomputing 2010, 73:2114-2124.
    • (2010) Neurocomputing , vol.73 , pp. 2114-2124
    • Hu, Q.H.1    Che, X.J.2    Zhang Lei, L.3
  • 9
    • 0036161259 scopus 로고    scopus 로고
    • Gene selection for cancer classification using support vector machines
    • Guyon I., Weston J., Barnhill S., Vapnik V. Gene selection for cancer classification using support vector machines. Mach. Learn. 2002, 46:389-422.
    • (2002) Mach. Learn. , vol.46 , pp. 389-422
    • Guyon, I.1    Weston, J.2    Barnhill, S.3    Vapnik, V.4
  • 10
    • 85161960219 scopus 로고    scopus 로고
    • Efficient and robust feature selection via joint l2,1-norms minimization, in: Neural Information Processing Systems, Canada
    • F.P. Nie, H. Huang, X. Cai, Efficient and robust feature selection via joint l2,1-norms minimization, in: Neural Information Processing Systems, Canada, 2010.
    • (2010)
    • Nie, F.P.1    Huang, H.2    Cai, X.3
  • 11
    • 84880862081 scopus 로고    scopus 로고
    • Neighborhood MinMax projections, in: Joint Conference on Artificial Intelligence, India
    • F.P. Nie, S.M. Xiang, C.S. Zhang, Neighborhood MinMax projections, in: Joint Conference on Artificial Intelligence, India, 2007.
    • (2007)
    • Nie, F.P.1    Xiang, S.M.2    Zhang, C.S.3
  • 12
    • 0038021028 scopus 로고    scopus 로고
    • A comparative study on feature selection and classification methods using gene expression profiles and proteomic patterns
    • Liu H., Li J., Wong L. A comparative study on feature selection and classification methods using gene expression profiles and proteomic patterns. Genome. Inform. 2002, 27:51-60.
    • (2002) Genome. Inform. , vol.27 , pp. 51-60
    • Liu, H.1    Li, J.2    Wong, L.3
  • 14
    • 57749182885 scopus 로고    scopus 로고
    • Trace ratio criterion for feature selection, in: 23rd AAAI Conference on Artificial Intelligence, Chicago
    • F. Nie, S. Xiang, Y. Jia, C. Zhang, S. Yan, Trace ratio criterion for feature selection, in: 23rd AAAI Conference on Artificial Intelligence, Chicago, 2008.
    • (2008)
    • Nie, F.1    Xiang, S.2    Jia, Y.3    Zhang, C.4    Yan, S.5
  • 15
    • 84864039505 scopus 로고    scopus 로고
    • Laplacian score for feature selection, in: Neural Information Processing Systems, Vancouver
    • X. He, D. Cai, P. Niyogi, Laplacian score for feature selection, in: Neural Information Processing Systems, Vancouver, 2005.
    • (2005)
    • He, X.1    Cai, D.2    Niyogi, P.3
  • 18
    • 36348982900 scopus 로고    scopus 로고
    • Marginal fisher analysis and its variants for human gait recognition and content-based image retrieval
    • Xu D., Yan S., Tao D., Lin S., Zhang H.J. Marginal fisher analysis and its variants for human gait recognition and content-based image retrieval. IEEE Trans. Image Process. 2007, 16:2811-2821.
    • (2007) IEEE Trans. Image Process. , vol.16 , pp. 2811-2821
    • Xu, D.1    Yan, S.2    Tao, D.3    Lin, S.4    Zhang, H.J.5
  • 19
    • 63149139219 scopus 로고    scopus 로고
    • Gene selection in cancer classification using PSO/SVM and GA/SVM hybrid algorithms, in: IEEE Congress on Evolutionary Computation, Singapore
    • E. Alba, N.J. Garcia, L. Jourdan, E.G. Talbi, Gene selection in cancer classification using PSO/SVM and GA/SVM hybrid algorithms, in: IEEE Congress on Evolutionary Computation, Singapore, 2007.
    • (2007)
    • Alba, E.1    Garcia, N.J.2    Jourdan, L.3    Talbi, E.G.4
  • 20
    • 84862166331 scopus 로고    scopus 로고
    • LIBSVM data sets
    • LIBSVM data sets. http://www.csie.ntu.edu.tw/~cjlin/libsvm/.
  • 21
    • 84862216612 scopus 로고    scopus 로고
    • UMIST database
    • UMIST database. http://www.sheffield.ac.uk/eee/research/iel/research/face.html.
  • 22
    • 84862183303 scopus 로고    scopus 로고
    • Yale univ. face database
    • Yale univ. face database. http://cvc.yale.edu/projects/yalefaces/yalefaces.html.
  • 23
    • 37549070399 scopus 로고    scopus 로고
    • Learning a maximum margin subspace for image retrieval
    • He X. Learning a maximum margin subspace for image retrieval. IEEE Trans. Knowl. Data Eng. 2008, 20:189-201.
    • (2008) IEEE Trans. Knowl. Data Eng. , vol.20 , pp. 189-201
    • He, X.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.