-
1
-
-
0346786584
-
Arcing classifiers
-
158
-
Breiman, L. (1998), "Arcing Classifiers," The Annals of Statistics, 26, 801-849. [158]
-
(1998)
The Annals of Statistics
, vol.26
, pp. 801-849
-
-
Breiman, L.1
-
2
-
-
0000275022
-
Prediction games and arcing algorithms
-
158
-
Breiman, L. (1999), "Prediction Games and Arcing Algorithms," Neural Computation, 11, 1493-1517. [158]
-
(1999)
Neural Computation
, vol.11
, pp. 1493-1517
-
-
Breiman, L.1
-
3
-
-
0035478854
-
Random forests
-
165
-
Breiman, L. (2001), "Random Forests," Machine Learning, 45, 5-32. [165]
-
(2001)
Machine Learning
, vol.45
, pp. 5-32
-
-
Breiman, L.1
-
4
-
-
33745157294
-
Boosting for high-dimensional linear models
-
158,161
-
Bühlmann, P. (2006), "Boosting for High-Dimensional Linear Models," The Annals of Statistics, 34, 559-583. [158,161]
-
(2006)
The Annals of Statistics
, vol.34
, pp. 559-583
-
-
Bühlmann, P.1
-
5
-
-
0043245810
-
Boosting with the L2 loss: Regression and classification
-
158,159,161
-
Bühlmann, P., and Yu, B. (2003), "Boosting With the L2 Loss: Regression and Classification," Journal of the American Statistical Association, 98, 324-339. [158,159,161]
-
(2003)
Journal of the American Statistical Association
, vol.98
, pp. 324-339
-
-
Bühlmann, P.1
Yu, B.2
-
6
-
-
2942714850
-
Rapid spectroscopic analysis of marzipan-comparative instrumentation
-
154,169,170,173
-
Christensen, J., Nørgaard, L., Heimdal, H., Pedersen, J. G., and Engelsen, S. B. (2004), "Rapid Spectroscopic Analysis of Marzipan-Comparative Instrumentation," Journal of Near Infrared Spectroscopy, 12, 63-75. [154,169,170,173]
-
(2004)
Journal of Near Infrared Spectroscopy
, vol.12
, pp. 63-75
-
-
Christensen, J.1
Nørgaard, L.2
Heimdal, H.3
Pedersen, J.G.4
Engelsen, S.B.5
-
7
-
-
3242708140
-
Least angle regression
-
164
-
Efron, B., Hastie, T., Johnstone, I., and Tibshirani, R. (2004), "Least Angle Regression," The Annals of Statistics, 32, 407-499. [164]
-
(2004)
The Annals of Statistics
, vol.32
, pp. 407-499
-
-
Efron, B.1
Hastie, T.2
Johnstone, I.3
Tibshirani, R.4
-
8
-
-
25444532788
-
Flexible smoothing with B-splines and penalties
-
172
-
Eilers, P. H. C., and Marx, B. D. (1996), "Flexible Smoothing With B-Splines and Penalties," Statistical Science, 11, 89-121. [172]
-
(1996)
Statistical Science
, vol.11
, pp. 89-121
-
-
Eilers, P.H.C.1
Marx, B.D.2
-
9
-
-
84952149204
-
A statistical view of some chemometrics regression tools" (with discussion
-
154
-
Frank, I. E., and Friedman, J. H. (1993), "A Statistical View of Some Chemometrics Regression Tools" (with discussion), Technometrics, 35, 109-148. [154]
-
(1993)
Technometrics
, vol.35
, pp. 109-148
-
-
Frank, I.E.1
Friedman, J.H.2
-
10
-
-
0002978642
-
Experiments with a new boosting algorithm
-
San Francisco, CA:Morgan Kaufmann, 158
-
Freund, Y., and Schapire, R. E. (1996), "Experiments With a New Boosting Algorithm," in Proceedings of the Thirteenth International Conference on Machine Learning, San Francisco, CA:Morgan Kaufmann, pp. 148-156. [158]
-
(1996)
Proceedings of the Thirteenth International Conference on Machine Learning
, pp. 148-156
-
-
Freund, Y.1
Schapire, R.E.2
-
12
-
-
0034164230
-
Additive logistic regression: A statistical view of boosting
-
158,173
-
Friedman, J. H., Hastie, T., and Tibshirani, R. (2000), "Additive Logistic Regression: A Statistical View of Boosting," The Annals of Statistics, 28, 337-407. [158,173]
-
(2000)
The Annals of Statistics
, vol.28
, pp. 337-407
-
-
Friedman, J.H.1
Hastie, T.2
Tibshirani, R.3
-
13
-
-
64549129955
-
Supervised feature selection in mass spectrometry based proteomic profiling by blockwise boosting
-
173
-
Gertheiss, J., and Tutz, G. (2009), "Supervised Feature Selection in Mass Spectrometry Based Proteomic Profiling by Blockwise Boosting," Bioinformatics, 25, 1076-1077. [173]
-
(2009)
Bioinformatics
, vol.25
, pp. 1076-1077
-
-
Gertheiss, J.1
Tutz, G.2
-
14
-
-
0000467952
-
Discussion of A statistical view of some chemometrics regression tools
-
by I. E. Frank and J. H. Friedman. 156
-
Hastie, T., and Mallows, C. (1993), Discussion of "A Statistical View of Some Chemometrics Regression Tools," by I. E. Frank and J. H. Friedman, Technometrics, 35, 140-143. [156]
-
(1993)
Technometrics
, vol.35
, pp. 140-143
-
-
Hastie, T.1
Mallows, C.2
-
15
-
-
84942484786
-
Ridge regression: Biased estimation for nonorthogonal problems
-
156-165
-
Hoerl, A. E., and Kennard, R. W. (1970), "Ridge Regression: Biased Estimation for Nonorthogonal Problems," Technometrics, 12, 55-67. [156,165]
-
(1970)
Technometrics
, vol.12
, pp. 55-67
-
-
Hoerl, A.E.1
Kennard, R.W.2
-
16
-
-
0001354983
-
Smoothing parameter selection in nonparametric regression using an improved akaike information criterion
-
161
-
Hurvich, C. M., Simonoff, J. S., and Tsai, C. (1998), "Smoothing Parameter Selection in Nonparametric Regression Using an Improved Akaike Information Criterion," Journal of the Royal Statistical Society, Ser. B, 60, 271-293. [161]
-
(1998)
Journal of the Royal Statistical Society, Ser. B
, vol.60
, pp. 271-293
-
-
Hurvich, C.M.1
Simonoff, J.S.2
Tsai, C.3
-
18
-
-
34250625424
-
-
Technical Report 656, Carnegie Mellon University Pittsburg, Dept. of Statistics. 157,158
-
Land, S. R., and Friedman, J. H. (1997), "Variable Fusion: A New Adaptive Signal Regression Method," Technical Report 656, Carnegie Mellon University Pittsburg, Dept. of Statistics. [157,158]
-
(1997)
Variable Fusion: A New Adaptive Signal Regression Method
-
-
Land, S.R.1
Friedman, J.H.2
-
20
-
-
0033079479
-
Genaralized linear regression on sampled signals and curves: A P-Spline approach
-
156,157,160,165,168,169,172
-
Marx, B. D., and Eilers, P. H. C. (1999), "Genaralized Linear Regression on Sampled Signals and Curves: A P-Spline Approach," Technometrics, 41, 1-13. [156,157,160,165,168,169,172]
-
(1999)
Technometrics
, vol.41
, pp. 1-13
-
-
Marx, B.D.1
Eilers, P.H.C.2
-
21
-
-
13444257535
-
Multidimensional penalized signal regression
-
156
-
Marx, B. D., and Eilers, P. H. C. (2005), "Multidimensional Penalized Signal Regression," Technometrics, 47, 13-22. [156]
-
(2005)
Technometrics
, vol.47
, pp. 13-22
-
-
Marx, B.D.1
Eilers, P.H.C.2
-
22
-
-
0000957593
-
Principal components regression in exploratory statistical research
-
164
-
Massy, W. F. (1965), "Principal Components Regression in Exploratory Statistical Research," Journal of the American Statistical Association, 60, 234-256. [164]
-
(1965)
Journal of the American Statistical Association
, vol.60
, pp. 234-256
-
-
Massy, W.F.1
-
23
-
-
1342340930
-
Near-infrared spectroscopy in food analysis
-
ed. R. A. Meyers, Chichester: Wiley. 169-170
-
Osborne, B. G. (2000), "Near-Infrared Spectroscopy in Food Analysis," in Encyclopedia of Analytical Chemistry, ed. R. A. Meyers, Chichester: Wiley. [169,170]
-
(2000)
Encyclopedia of Analytical Chemistry
-
-
Osborne, B.G.1
-
24
-
-
84884285374
-
R development core team
-
Vienna, Austria: R Foundation for Statistical Computing. 164
-
R Development Core Team (2007), R: A Language and Environment for Statistical Computing, Vienna, Austria: R Foundation for Statistical Computing. [164]
-
(2007)
R A Language and Environment for Statistical Computing
-
-
-
25
-
-
0004130505
-
-
(2nd ed.), New York: Springer. 154-157, 165,167,168,172,173
-
Ramsay, J. O., and Silverman, B. W. (2005), Functional Data Analysis (2nd ed.), New York: Springer. [154-157, 165,167,168,172,173]
-
(2005)
Functional Data Analysis
-
-
Ramsay, J.O.1
Silverman, B.W.2
-
26
-
-
0025448521
-
The strength of weak learnability
-
158
-
Schapire, R. E. (1990), "The Strength of Weak Learnability," Machine Learning, 5, 197-227. [158]
-
(1990)
Machine Learning
, vol.5
, pp. 197-227
-
-
Schapire, R.E.1
-
27
-
-
85194972808
-
Regression shrinkage and selection via the lasso
-
156,157.164
-
Tibshirani, R. (1996), "Regression Shrinkage and Selection via the Lasso," Journal of the Royal Statistical Society, Ser. B, 58, 267-288. [156,157,164]
-
(1996)
Journal of the Royal Statistical Society, Ser. B
, vol.58
, pp. 267-288
-
-
Tibshirani, R.1
-
28
-
-
12844266177
-
Sparsity and smoothness via the fused lasso
-
156,158,165.170
-
Tibshirani, R., Saunders, M., Rosset, S., Zhu, J., and Kneight, K. (2005), "Sparsity and Smoothness via the Fused Lasso," Journal of the Royal Statistical Society, Ser. B, 67, 91-108. [156,158,165,170]
-
(2005)
Journal of the Royal Statistical Society, Ser. B
, vol.67
, pp. 91-108
-
-
Tibshirani, R.1
Saunders, M.2
Rosset, S.3
Zhu, J.4
Kneight, K.5
-
29
-
-
0002692783
-
Soft modeling by latent variables: The nonlinear partial least squares approach
-
ed. J. Gani, London: Academic Press. 164
-
Wold, H. (1975), "Soft Modeling by Latent Variables: The Nonlinear Partial Least Squares Approach," in Perspectives in Probability and Statistics, Papers in Honour of M. S. Bartlett, ed. J. Gani, London: Academic Press. [164]
-
(1975)
Perspectives in Probability and Statistics, Papers in Honour of M. S. Bartlett
-
-
Wold, H.1
-
30
-
-
16244401458
-
Regularization and variable selection via the elastic net
-
156,165
-
Zou, H., and Hastie, T. (2005), "Regularization and Variable Selection via the Elastic Net," Journal of the Royal Statistical Society, Ser. B, 67, 301-320. [156,165]
-
(2005)
Journal of the Royal Statistical Society, Ser. B
, vol.67
, pp. 301-320
-
-
Zou, H.1
Hastie, T.2
|