-
1
-
-
33745561205
-
An introduction to variable and feature selection
-
Guyon I, Elisseeff A: An introduction to variable and feature selection.J Machine Learning Res 2003, 3:1157–1182.
-
(2003)
J Machine Learning Res
, vol.3
, pp. 1157-1182
-
-
Guyon, I.1
Elisseeff, A.2
-
2
-
-
35748932917
-
A review of feature selection techniques in bioinformatics
-
Saeys Y, Inza I, Larraage P: A review of feature selection techniques in bioinformatics.Bioinformatics 2007,23(19):2507–2517.
-
(2007)
Bioinformatics
, vol.23
, Issue.19
, pp. 2507-2517
-
-
Saeys, Y.1
Inza, I.2
Larraage, P.3
-
3
-
-
3042532685
-
Filter versus warpper gene selection approaches in dna microarray domains
-
Inza I, Larranaga P, Blanco R, Cerrolaza A: Filter versus warpper gene selection approaches in dna microarray domains.Artif Intelligence Med 2004, 31:91–103.
-
(2004)
Artif Intelligence Med
, vol.31
, pp. 91-103
-
-
Inza, I.1
Larranaga, P.2
Blanco, R.3
Cerrolaza, A.4
-
4
-
-
49949090353
-
Penalized feature selection and classification in bioinformatics
-
Ma S, Huang J: Penalized feature selection and classification in bioinformatics.Brief Bioinfrom 2008,9(5):392–403.
-
(2008)
Brief Bioinfrom
, vol.9
, Issue.5
, pp. 392-403
-
-
Ma, S.1
Huang, J.2
-
5
-
-
79957591684
-
Improving feature selection algorithms using normalised feature histograms
-
James AP, Maan A: Improving feature selection algorithms using normalised feature histograms.IET Electron lett 2011,47(8):490–491.
-
(2011)
IET Electron lett
, vol.47
, Issue.8
, pp. 490-491
-
-
James, A.P.1
Maan, A.2
-
7
-
-
33744552752
-
Formost large underdetermined systems of linear equations, the minimal l1-norm solution is also the sparest solution
-
Donoho D: Formost large underdetermined systems of linear equations, the minimal l1-norm solution is also the sparest solution.Comm Pure Appl Math 2006, 59:907–934.
-
(2006)
Comm Pure Appl Math
, vol.59
, pp. 907-934
-
-
Donoho, D.1
-
8
-
-
70449440300
-
Ultrahigh dimensional feature selection: Beyond the linear model
-
Fan J, Samworth R, Wu Y: Ultrahigh dimensional feature selection: Beyond the linear model.J Machine Learning Res 2009, 10:2013–2038.
-
(2009)
J Machine Learning Res
, vol.10
, pp. 2013-2038
-
-
Fan, J.1
Samworth, R.2
Wu, Y.3
-
11
-
-
84865779001
-
Nearest Neighbor Classifier Based on Nearest Feature Decisions
-
James AP, Dimitrijev S: Nearest Neighbor Classifier Based on Nearest Feature Decisions.Comput J 2012. doi:10.1093/comjnl/bxs001
-
(2012)
Comput J
-
-
James, A.P.1
Dimitrijev, S.2
-
12
-
-
77957017440
-
Inter-image outliers and their application to image classification
-
James A, Dimitrijev S: Inter-image outliers and their application to image classification.Pattern Recognit 2010,43(12):4101–4112.
-
(2010)
Pattern Recognit
, vol.43
, Issue.12
, pp. 4101-4112
-
-
James, A.1
Dimitrijev, S.2
-
14
-
-
53749107899
-
Dimensionality reduction based on rough set theory: A review
-
Thangavel K, Pethalakshmi A: Dimensionality reduction based on rough set theory: A review.Appl Soft Comput 2009,9(1):1–12.
-
(2009)
Appl Soft Comput
, vol.9
, Issue.1
, pp. 1-12
-
-
Thangavel, K.1
Pethalakshmi, A.2
-
16
-
-
80053402499
-
-
Zhao Z, Wang J, Sharma S, Agarwal N, Liu H, Chang Y: An intergrative approach to identifying biologically relevant genes. 2010, pp 838–849.
-
(2010)
An intergrative approach to identifying biologically relevant genes
, pp. pp 838-pp 849
-
-
Zhao, Z.1
Wang, J.2
Sharma, S.3
Agarwal, N.4
Liu, H.5
Chang, Y.6
-
17
-
-
17044405923
-
Toward intergrating feature selection algorithms for classification and clustering
-
Liu H, Yu L: Toward intergrating feature selection algorithms for classification and clustering.IEEE Transactions Knowledge Data Eng 2005,17(3):1–12.
-
(2005)
IEEE Transactions Knowledge Data Eng
, vol.17
, Issue.3
, pp. 1-12
-
-
Liu, H.1
Yu, L.2
-
18
-
-
7244248755
-
A comparative study of feature selection and multiclass classification methods for tissue classification based on gene expressions
-
Li T, Zhang C, Ogihara M: A comparative study of feature selection and multiclass classification methods for tissue classification based on gene expressions.Bioinformatics 2004,20(15):2429–2437.
-
(2004)
Bioinformatics
, vol.20
, Issue.15
, pp. 2429-2437
-
-
Li, T.1
Zhang, C.2
Ogihara, M.3
-
19
-
-
0038021028
-
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.Genone Inform 2002, 13:51–60.
-
(2002)
Genone Inform
, vol.13
, pp. 51-60
-
-
Liu, H.1
Li, J.2
Wong, L.3
-
20
-
-
0141990695
-
Theoritical and emperical analysis of Relief and Relief
-
Sikonja MR, Kononenko I: Theoritical and emperical analysis of Relief and Relief.Machine Learning 2003, 53:23–69.
-
(2003)
Machine Learning
, vol.53
, pp. 23-69
-
-
Sikonja, M.R.1
Kononenko, I.2
-
21
-
-
84890520049
-
Use of the zero norm with linear models and kernel methods
-
Weston J, Elisseff A, Schoelkopf B, Tipping M: Use of the zero norm with linear models and kernel methods.J Machine Learning Res 2003, 3:1439–1461.
-
(2003)
J Machine Learning Res
, vol.3
, pp. 1439-1461
-
-
Weston, J.1
Elisseff, A.2
Schoelkopf, B.3
Tipping, M.4
-
22
-
-
34547964410
-
-
ACM New York, USA, pp 823–830
-
Song L, Smola A, Gretton A, Brogwardt K, Bedo J: Supervised feature selection via dependence estimation. 2007.
-
(2007)
Supervised feature selection via dependence estimation
-
-
Song, L.1
Smola, A.2
Gretton, A.3
Brogwardt, K.4
Bedo, J.5
-
23
-
-
3242708140
-
Least angle regression
-
Efron B, Hastie T, Johnstone I, Tibshirani R: Least angle regression.Ann Stat 2004, 32:407–449.
-
(2004)
Ann Stat
, vol.32
, pp. 407-449
-
-
Efron, B.1
Hastie, T.2
Johnstone, I.3
Tibshirani, R.4
-
28
-
-
0031381525
-
Wrappers for Feature Subset Selection
-
Kohavi R, John G: Wrappers for Feature Subset Selection.Artif Intelligence 1997,97(1–2):273–324.
-
(1997)
Artif Intelligence
, vol.97
, Issue.1-2
, pp. 273-324
-
-
Kohavi, R.1
John, G.2
-
32
-
-
0013326060
-
Feature selection for classification
-
Dash M, Liu H: Feature selection for classification.Intell Data Anal 1997,1(3):131–156.
-
(1997)
Intell Data Anal
, vol.1
, Issue.3
, pp. 131-156
-
-
Dash, M.1
Liu, H.2
-
33
-
-
0017535866
-
Branch and bound algorithm for feature subset selection
-
Narendra PM, Fukunaga K: Branch and bound algorithm for feature subset selection.IEEE Trans Comput 1977,26(9):917–922.
-
(1977)
IEEE Trans Comput
, vol.26
, Issue.9
, pp. 917-922
-
-
Narendra, P.M.1
Fukunaga, K.2
-
36
-
-
0028496468
-
Learning boolean concepts in the presence of many irrelavent features
-
Almuallim H, Dietterich TG: Learning boolean concepts in the presence of many irrelavent features.Artif Intelligence 1994,69(1–2):278–305.
-
(1994)
Artif Intelligence
, vol.69
, Issue.1-2
, pp. 278-305
-
-
Almuallim, H.1
Dietterich, T.G.2
-
38
-
-
0031334221
-
Selection of relevant features and examples in machine learning
-
Blum AL, Langley P: Selection of relevant features and examples in machine learning.Artif Intelligence 1997, 97:245–271.
-
(1997)
Artif Intelligence
, vol.97
, pp. 245-271
-
-
Blum, A.L.1
Langley, P.2
-
42
-
-
0031078007
-
Feature selection: evaluation, application, and small sample performance
-
Jain A, Zongker D: Feature selection: evaluation, application, and small sample performance.IEEE Trans Pattern Anal Mach Intell 1997, 19:153–158.
-
(1997)
IEEE Trans Pattern Anal Mach Intell
, vol.19
, pp. 153-158
-
-
Jain, A.1
Zongker, D.2
-
43
-
-
0026453958
-
Training a 3-Node Neural Networks in NP-Complete
-
Blum A, Rivest R: Training a 3-Node Neural Networks in NP-Complete.Neural Networks 1992, 5:117–127.
-
(1992)
Neural Networks
, vol.5
, pp. 117-127
-
-
Blum, A.1
Rivest, R.2
-
45
-
-
0032072963
-
Feature selection by analysing class regions approximated by ellipsoids
-
Abe S, Thawonmas R, Kobayashi Y: Feature selection by analysing class regions approximated by ellipsoids.IEEE Trans Syst, Man Cybernetics– Part C: App Rev 1998, 28:282–287.
-
(1998)
IEEE Trans Syst, Man Cybernetics– Part C: App Rev
, vol.28
, pp. 282-287
-
-
Abe, S.1
Thawonmas, R.2
Kobayashi, Y.3
-
46
-
-
30044438683
-
Combined SVM-based feature selection and classification
-
Neumann J, Schnorr C, Steidl G: Combined SVM-based feature selection and classification.Machine Learning 2005, 61:129–150.
-
(2005)
Machine Learning
, vol.61
, pp. 129-150
-
-
Neumann, J.1
Schnorr, C.2
Steidl, G.3
-
47
-
-
77954565155
-
Discriminative semisupervised feature selection via manifold regularization
-
Xu Z, King I, Lyu MR-T, Jin R: Discriminative semisupervised feature selection via manifold regularization.IEEE Trans. on Neural Networks 2010,21(7):1033–1047.
-
(2010)
IEEE Trans. on Neural Networks
, vol.21
, Issue.7
, pp. 1033-1047
-
-
Xu, Z.1
King, I.2
Lyu, M.R.-T.3
Jin, R.4
-
48
-
-
4644313275
-
Gene expression profiling of gliomas strongly predicts survival
-
Freije WA, Castro-Vargas FE, Fang Z, Horvath S, Cloughesy T, Liau LM, Mischel PS, Nelson SF: Gene expression profiling of gliomas strongly predicts survival.Cancer Res 2004,64(18):6503–6510.
-
(2004)
Cancer Res
, vol.64
, Issue.18
, pp. 6503-6510
-
-
Freije, W.A.1
Castro-Vargas, F.E.2
Fang, Z.3
Horvath, S.4
Cloughesy, T.5
Liau, L.M.6
Mischel, P.S.7
Nelson, S.F.8
-
49
-
-
33645772227
-
Neuronal and glioma-derived stem cell factor induces angiogenesis within the brain
-
Sun L, Hui AM, Su Q, Vortmeyer A, Kotliarov Y, Pastorino S, James AP: Neuronal and glioma-derived stem cell factor induces angiogenesis within the brain.Cancer Cell 2006,9(4):287–300.
-
(2006)
Cancer Cell
, vol.9
, Issue.4
, pp. 287-300
-
-
Sun, L.1
Hui, A.M.2
Su, Q.3
Vortmeyer, A.4
Kotliarov, Y.5
Pastorino, S.6
James, A.P.7
-
50
-
-
5444276626
-
Microarray gene expression profiling of B-cell chronic lymphocytic leukemia subgroups defined by genomic aberrations and VH mutation status
-
Haslinger C, Schweifer N, Stilgenbauer S, Dhner H, Lichter P, Kraut N, Stratowa C, Abseher R: Microarray gene expression profiling of B-cell chronic lymphocytic leukemia subgroups defined by genomic aberrations and VH mutation status.J Clin Oncol 2004,22(19):3937–3949.
-
(2004)
J Clin Oncol
, vol.22
, Issue.19
, pp. 3937-3949
-
-
Haslinger, C.1
Schweifer, N.2
Stilgenbauer, S.3
Dhner, H.4
Lichter, P.5
Kraut, N.6
Stratowa, C.7
Abseher, R.8
-
51
-
-
77953037177
-
Ovo1 links Wnt signaling with N-cadherin localization during neural crest migration
-
Piloto S, Schilling T: Ovo1 links Wnt signaling with N-cadherin localization during neural crest migration.Development 2010,137(12):1981–1990.
-
(2010)
Development
, vol.137
, Issue.12
, pp. 1981-1990
-
-
Piloto, S.1
Schilling, T.2
-
52
-
-
33847749502
-
Airway epithelial gene expression in the diagnostic evaluation of smokers with suspect lung cancer
-
Spira A, Beane JE, Shah V, Steiling K, Liu G, Schembri F, Gilman S, Dumas YM, Calner P, Sebastiani P, Sridhar S, Beamis J, Lamb C, Anderson T, Gerry N, Keane J, Lenburg ME, Brody JS: Airway epithelial gene expression in the diagnostic evaluation of smokers with suspect lung cancer.Nat Med 2007,13(3):361–366.
-
(2007)
Nat Med
, vol.13
, Issue.3
, pp. 361-366
-
-
Spira, A.1
Beane, J.E.2
Shah, V.3
Steiling, K.4
Liu, G.5
Schembri, F.6
Gilman, S.7
Dumas, Y.M.8
Calner, P.9
Sebastiani, P.10
Sridhar, S.11
Beamis, J.12
Lamb, C.13
Anderson, T.14
Gerry, N.15
Keane, J.16
Lenburg, M.E.17
Brody, J.S.18
-
53
-
-
24344458137
-
Feature selection based on mutual information: criteria of max-dependency, max-relevance, and min-redundancy
-
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 Machine Intell 2005,27(8):1226–1238.
-
(2005)
IEEE Trans Pattern Anal Machine Intell
, vol.27
, Issue.8
, pp. 1226-1238
-
-
Peng, H.1
Long, F.2
Ding, C.3
|