-
1
-
-
0002662712
-
On the existence of maximum likelihood estimates in logistic regression models
-
Albert A., and Anderson J.A. On the existence of maximum likelihood estimates in logistic regression models. Biometrika 71 (1984) 1-10
-
(1984)
Biometrika
, vol.71
, pp. 1-10
-
-
Albert, A.1
Anderson, J.A.2
-
2
-
-
34147105062
-
-
Allison, D.P., 1999. Logistic regression using the SAS system: theory and application, SAS institute, ISBN: 1-58025-352-0.
-
-
-
-
3
-
-
31844446681
-
-
Bach, F.R., Jordan, M.I., 2005. Predictive low-rank decomposition for kernel methods. In: Proceedings of the Twenty-second International Conference on Machine Learning, Bonn, Germany.
-
-
-
-
4
-
-
0033544443
-
Non-linear projection to latent structures revisited (the neural networks PLS algorithm)
-
Baffi G., Martin E.B., and Morris A.J. Non-linear projection to latent structures revisited (the neural networks PLS algorithm). Comput. Chem. Eng. 23 (1999) 1293-1307
-
(1999)
Comput. Chem. Eng.
, vol.23
, pp. 1293-1307
-
-
Baffi, G.1
Martin, E.B.2
Morris, A.J.3
-
5
-
-
0037350844
-
Partial least squares for discrimination
-
Barker M., and Rayens W.S. Partial least squares for discrimination. J. Chemometrics 17 (2003) 166-173
-
(2003)
J. Chemometrics
, vol.17
, pp. 166-173
-
-
Barker, M.1
Rayens, W.S.2
-
7
-
-
2442514721
-
An optimization perspective on kernel partial least squares regression
-
IOS Press, Amsterdam
-
Bennett K.P., and Embrechts M.J. An optimization perspective on kernel partial least squares regression. Advances in Learning Theory: Methods, Models and Applications. NATO Sciences Series III: Computer and Systems Sciences vol. 190 (2003), IOS Press, Amsterdam 227-250
-
(2003)
Advances in Learning Theory: Methods, Models and Applications. NATO Sciences Series III: Computer and Systems Sciences
, vol.190
, pp. 227-250
-
-
Bennett, K.P.1
Embrechts, M.J.2
-
8
-
-
0026966646
-
-
Boser, B.E., Guyon, I., Vapnik, V.N., 1992. A training algorithm for optimal margin classifiers. In: Proceedings of the Fifth Annual Workshop on Computational Learning Theory, vol. 5, Pittsburgh, pp. 144-152.
-
-
-
-
9
-
-
27144489164
-
A tutorial on support vector machines for pattern recognition
-
Burges C.J.C. A tutorial on support vector machines for pattern recognition. Data Mining and Knowledge Discovery 2 2 (1998) 121-167
-
(1998)
Data Mining and Knowledge Discovery
, vol.2
, Issue.2
, pp. 121-167
-
-
Burges, C.J.C.1
-
11
-
-
34249753618
-
Support vector network
-
Cortes C., and Vapnik V. Support vector network. Mach. Learning 20 (1995) 273-297
-
(1995)
Mach. Learning
, vol.20
, pp. 273-297
-
-
Cortes, C.1
Vapnik, V.2
-
12
-
-
0034419669
-
Regularization networks and support vector machines
-
Evgeniou T., Pontil M., and Poggio T. Regularization networks and support vector machines. Adv. Comput. Math. 13 (1999) 1-50
-
(1999)
Adv. Comput. Math.
, vol.13
, pp. 1-50
-
-
Evgeniou, T.1
Pontil, M.2
Poggio, T.3
-
13
-
-
0002178053
-
Bias reduction of maximum likelihood estimates
-
Firth D. Bias reduction of maximum likelihood estimates. Biometrika 80 (1993) 27-38
-
(1993)
Biometrika
, vol.80
, pp. 27-38
-
-
Firth, D.1
-
14
-
-
21344479527
-
An interpretation of partial least squares
-
Garthwaite P.H. An interpretation of partial least squares. J. Amer. Statist. Assoc. 89 425 (1994) 122-127
-
(1994)
J. Amer. Statist. Assoc.
, vol.89
, Issue.425
, pp. 122-127
-
-
Garthwaite, P.H.1
-
15
-
-
0024443297
-
Receiver operating characteristic methodology: the state of the art
-
Hanley J.A. Receiver operating characteristic methodology: the state of the art. Critical Reviews in Diagnostic Imaging 29 (1989) 307-335
-
(1989)
Critical Reviews in Diagnostic Imaging
, vol.29
, pp. 307-335
-
-
Hanley, J.A.1
-
16
-
-
0037199788
-
A solution to the problem of separation in logistic regression
-
Heinze G., and Schemper M. A solution to the problem of separation in logistic regression. Statist. Medicine 21 (2002) 2409-2419
-
(2002)
Statist. Medicine
, vol.21
, pp. 2409-2419
-
-
Heinze, G.1
Schemper, M.2
-
17
-
-
85162676194
-
PLS regression methods
-
Höskuldsson A. PLS regression methods. J. Chemometrics 2 (1988) 211-228
-
(1988)
J. Chemometrics
, vol.2
, pp. 211-228
-
-
Höskuldsson, A.1
-
18
-
-
0002714543
-
Making large-scale SVM learning practical
-
Schölkopf B., Burges C., and Smola A. (Eds), MIT Press, Cambridge, MA
-
Joachims J. Making large-scale SVM learning practical. In: Schölkopf B., Burges C., and Smola A. (Eds). Advances in Kernel Methods-Support Vector Learning (1999), MIT Press, Cambridge, MA
-
(1999)
Advances in Kernel Methods-Support Vector Learning
-
-
Joachims, J.1
-
19
-
-
34147156329
-
-
Li, J., Liu, H., 2002. Kent Ridge Biomedical Dataset Repository. 〈http://sdmc-lit.org.sg/GEDatasets〉
-
-
-
-
21
-
-
0038259120
-
Kernel partial least squares regression in reproducing kernel hilbert space
-
Rosipal R., and Trejo L.J. Kernel partial least squares regression in reproducing kernel hilbert space. J. Mach. Learning Res. 2 (2001) 97-123
-
(2001)
J. Mach. Learning Res.
, vol.2
, pp. 97-123
-
-
Rosipal, R.1
Trejo, L.J.2
-
22
-
-
1942516826
-
-
Rosipal, R., Trejo, L.J., Matthews, B., 2003. Kernel PLS-SVC for linear and nonlinear classification. In: Proceeding of the Twentieth International Conference on Machine Learning, Washington, USA.
-
-
-
-
24
-
-
0347243182
-
Nonlinear component analysis as a kernel eigenvalue problem
-
Schölkopf B., Smola A.J., and Müller K.R. Nonlinear component analysis as a kernel eigenvalue problem. Neural Comput. 10 (1998) 1299-1319
-
(1998)
Neural Comput.
, vol.10
, pp. 1299-1319
-
-
Schölkopf, B.1
Smola, A.J.2
Müller, K.R.3
-
26
-
-
22944456563
-
Dimension reduction-based penalized logistic regression for cancer classification using microarray data
-
Shen L., and Tan E.C. Dimension reduction-based penalized logistic regression for cancer classification using microarray data. IEEE/ACM Trans. Comput. Biol. Bioinformatics 2 2 (2005) 166-175
-
(2005)
IEEE/ACM Trans. Comput. Biol. Bioinformatics
, vol.2
, Issue.2
, pp. 166-175
-
-
Shen, L.1
Tan, E.C.2
-
27
-
-
34147116854
-
-
Smola, A.J., Schölkopf, B., 2000. Sparse greedy matrix approximation for machine learning. In: Proceeding of the Seventeenth International Conference on Machine Learning, Stanford, USA.
-
-
-
-
29
-
-
34147128773
-
-
Tenenhaus, M., 1998. La Régression PLS, éditions Technip.
-
-
-
-
30
-
-
34147179579
-
La régression logistique PLS
-
Droesbeke J.J., Lejeune M., and Saporta G. (Eds), Editions Technip
-
Tenenhaus M. La régression logistique PLS. In: Droesbeke J.J., Lejeune M., and Saporta G. (Eds). Modèles statistiques pour données qualitatives (2005), Editions Technip
-
(2005)
Modèles statistiques pour données qualitatives
-
-
Tenenhaus, M.1
-
31
-
-
34147164155
-
-
Tenenhaus, A., Giron, A., Saporta, G., Fertil, B., 2005. Kernel logistic PLS: a new tool for complex classification. In: 11th International Symposium on Applied Stochastic Models and Data Analysis, Brest, France.
-
-
-
-
33
-
-
0000503256
-
An inter-battery method of factor analysis
-
Tucker L.R. An inter-battery method of factor analysis. Psychometrika 23 2 (1958)
-
(1958)
Psychometrika
, vol.23
, Issue.2
-
-
Tucker, L.R.1
-
35
-
-
34147108354
-
-
Wahba, G., 1999. Support vector machines, reproducing kernel Hilbert spaces and randomized GACV. In: Advances in Kernel Methods-Support Vector Learning, pp. 69-88.
-
-
-
-
36
-
-
0003972765
-
-
Webb, A.R., 1996. Nonlinear feature extraction with radial basis functions using a weighted multidimensional scaling stress measure. In: 13th International Conference on Pattern Recognition.
-
-
-
-
37
-
-
34147139560
-
-
Williams, C.K.I., Seeger, M., 2000. Effect on the input density distribution on kernel-based classifiers. In: Proceeding of the Seventeenth International Conference on Machine Learning, Stanford, USA.
-
-
-
-
38
-
-
0026578543
-
Non-linear partial least squares modelling. II Spline inner function
-
Wold S. Non-linear partial least squares modelling. II Spline inner function. Chemometrics Intell. Lab. Systems 14 (1992) 71-84
-
(1992)
Chemometrics Intell. Lab. Systems
, vol.14
, pp. 71-84
-
-
Wold, S.1
-
39
-
-
0002555784
-
The multivariate calibration problem in chemistry solved by the PLS method
-
Springer, Heidelberg
-
Wold S., Martens H., and Wold H. The multivariate calibration problem in chemistry solved by the PLS method. Lecture Notes in Mathematics (1983), Springer, Heidelberg 286-293
-
(1983)
Lecture Notes in Mathematics
, pp. 286-293
-
-
Wold, S.1
Martens, H.2
Wold, H.3
-
41
-
-
0030814744
-
The kernel PCA algorithms for wide data. Part II: fast cross validation and application in classification of NIR data
-
Wu W., Massart D.L., and de Jong S. The kernel PCA algorithms for wide data. Part II: fast cross validation and application in classification of NIR data. Chemometrics Intell. Lab. Systems 37 (1997) 271-280
-
(1997)
Chemometrics Intell. Lab. Systems
, vol.37
, pp. 271-280
-
-
Wu, W.1
Massart, D.L.2
de Jong, S.3
-
42
-
-
15944424353
-
Kernel logistic regression and the import vector machine
-
Zhu J., and Hastie T. Kernel logistic regression and the import vector machine. J. Comput. Graphical Statist. 14 1 (2005) 185-205
-
(2005)
J. Comput. Graphical Statist.
, vol.14
, Issue.1
, pp. 185-205
-
-
Zhu, J.1
Hastie, T.2
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