-
1
-
-
0033931867
-
Assessing the Accuracy of Prediction Algorithms for Classification: An Overview
-
P. Baldi, S. Brunak, Y. Chauvin, C. Andersen, and H. Nielsen, Assessing the Accuracy of Prediction Algorithms for Classification: an Overview, Bioinformatics 16, pp. 412-424, 2000.
-
(2000)
Bioinformatics
, vol.16
, pp. 412-424
-
-
Baldi, P.1
Brunak, S.2
Chauvin, Y.3
Andersen, C.4
Nielsen, H.5
-
2
-
-
0032645080
-
An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Variants
-
E. Bauer and R. Kohavi, An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Variants, Machine Learning 36, pp. 105-139, 1999.
-
(1999)
Machine Learning
, vol.36
, pp. 105-139
-
-
Bauer, E.1
Kohavi, R.2
-
3
-
-
0001526276
-
Improving the Accuracy of an Artificial Neural Network using Multiple Differently Trained Networks
-
W. Baxt, Improving the Accuracy of an Artificial Neural Network using Multiple Differently Trained Networks, Neural Computation 4, pp. 772-780, 1992.
-
(1992)
Neural Computation
, vol.4
, pp. 772-780
-
-
Baxt, W.1
-
4
-
-
84942937534
-
Symbolic Rule Extraction from the DIMLP Neural Network
-
S. Wermter and R. Sun, eds. Springer Verlag
-
G. Bologna, Symbolic Rule Extraction from the DIMLP Neural Network, Neural Hybrid Systems, S. Wermter and R. Sun, eds. Springer Verlag, pp. 240-254, 2000.
-
(2000)
Neural Hybrid Systems
, pp. 240-254
-
-
Bologna, G.1
-
5
-
-
84971610592
-
A Model for Single and Multiple Knowledge Based Networks
-
G. Bologna, A Model for Single and Multiple Knowledge Based Networks, Artificial Intelligence in Medicine, To appear.
-
Artificial Intelligence in Medicine
-
-
Bologna, G.1
-
6
-
-
0030211964
-
Bagging Predictors
-
L. Breiman, Bagging Predictors, Machine Learning 26, pp. 123-140, 1996.
-
(1996)
Machine Learning
, vol.26
, pp. 123-140
-
-
Breiman, L.1
-
7
-
-
0003619255
-
-
Technical Report Statistics Department, University of California
-
L. Breiman, Bias, Variance, and Arcing Classifiers. Technical Report 460, Statistics Department, University of California (available at ftp://ftp.stat.berkeley.edu/pub/users/breiman/), 1996.
-
(1996)
Bias, Variance, and Arcing Classifiers
-
-
Breiman, L.1
-
8
-
-
0035014847
-
Multi-Class Protein Fold Recognition Using Support Vector Machines and Neural Networks
-
C.H.Q. Ding, and I. Dubchak, Multi-Class Protein Fold Recognition Using Support Vector Machines and Neural Networks, Bioinformatics 17 (4), pp. 349-358, 2001.
-
(2001)
Bioinformatics
, vol.17
, Issue.4
, pp. 349-358
-
-
Ding, C.H.Q.1
Dubchak, I.2
-
9
-
-
0029047319
-
Prediction of Protein Folding Class using Global Description of Amino Acid Sequence
-
I. Dubchak, I. Muchnik, S.R. Holbrook, and S.H. Kim, Prediction of Protein Folding Class using Global Description of Amino Acid Sequence, Proc. Natl Acad Sci. 92, pp. 8700-8704, 1995.
-
(1995)
Proc. Natl Acad Sci.
, vol.92
, pp. 8700-8704
-
-
Dubchak, I.1
Muchnik, I.2
Holbrook, S.R.3
Kim, S.H.4
-
11
-
-
0027092678
-
Selection of a Representative Set of Structures from the Brookhaven Protein Bank
-
U. Hobohm, M. Scharf, R. Schneider, and C. Sander, Selection of a Representative Set of Structures from the Brookhaven Protein Bank, Protein Science 3, pp. 409-417, 1992.
-
(1992)
Protein Science
, vol.3
, pp. 409-417
-
-
Hobohm, U.1
Scharf, M.2
Schneider, R.3
Sander, C.4
-
12
-
-
0028205447
-
Enlarged Representative Set of Proteins
-
U. Hobohm, and C. Sander, Enlarged Representative Set of Proteins, Protein Science 3, pp. 522-524, 1994.
-
(1994)
Protein Science
, vol.3
, pp. 522-524
-
-
Hobohm, U.1
Sander, C.2
-
13
-
-
0033977962
-
SCOP: A Structural Classification of Proteins Database
-
L. Lo Conte, B. Ailey, T.J.P Hubbard, S.E. Brenner, A.G. Murzin, and C. Chotia, SCOP: a Structural Classification of Proteins Database, Nucleic Acids Research 28, pp. 257-259, 2000.
-
(2000)
Nucleic Acids Research
, vol.28
, pp. 257-259
-
-
Lo Conte, L.1
Ailey, B.2
Hubbard, T.J.P.3
Brenner, S.E.4
Murzin, A.G.5
Chotia, C.6
-
14
-
-
0000551189
-
Popular Ensemble Methods: An Empirical Study
-
D. Opitz, and R. Maclin, Popular Ensemble Methods: An Empirical Study, Artificial Intelligence Research 11, pp. 169-198, 1999.
-
(1999)
Artificial Intelligence Research
, vol.11
, pp. 169-198
-
-
Opitz, D.1
Maclin, R.2
|