-
1
-
-
0001918655
-
Feature selection for case-based classification of cloud types: An empirical comparision
-
Seattle, WA, AAAI Press
-
D. W. Aha and R. L. Bankert. Feature selection for case-based classification of cloud types: An empirical comparision. In Working Notes of the AAAI-94 Workshop on Case-Based Reasoning, pages 106-112, Seattle, WA, 1994. AAAI Press.
-
(1994)
Working Notes of the AAAI-94 Workshop on Case-based Reasoning
, pp. 106-112
-
-
Aha, D.W.1
Bankert, R.L.2
-
3
-
-
0003408496
-
-
Technical report, University of California, Department of Information and Computer Science
-
C. L. Blake and C. J. Merz. Uci repository of machine learning databases. Technical report, University of California, Department of Information and Computer Science, 1998.
-
(1998)
Uci Repository of Machine Learning Databases
-
-
Blake, C.L.1
Merz, C.J.2
-
9
-
-
0031069985
-
Context sensitive feature selection for lazy learners
-
P. Domingos. Context sensitive feature selection for lazy learners. Artificial Intelligence Review, 11:227-253, 1997.
-
(1997)
Artificial Intelligence Review
, vol.11
, pp. 227-253
-
-
Domingos, P.1
-
11
-
-
0038821242
-
-
Technical Report, Stanford University, Department of Statistics
-
B. Efron, T. Hastie, I. Johnstone, and R. Tibsharini. Least angle regression. Technical Report TR-220, Stanford University, Department of Statistics, 2003.
-
(2003)
Least Angle Regression
-
-
Efron, B.1
Hastie, T.2
Johnstone, I.3
Tibsharini, R.4
-
13
-
-
0027294340
-
Improving model selection by nonconvergent methods
-
W. Finnoff, F. Hergert, and H. G. Zimmermann. Improving model selection by nonconvergent methods. Neural Networks, 6:771-783, 1993.
-
(1993)
Neural Networks
, vol.6
, pp. 771-783
-
-
Finnoff, W.1
Hergert, F.2
Zimmermann, H.G.3
-
14
-
-
0007133880
-
A "thermal" perceptron learning rule
-
M. Frean. A "thermal" perceptron learning rule. Neural Computation, 4(6):946-957, 1992.
-
(1992)
Neural Computation
, vol.4
, Issue.6
, pp. 946-957
-
-
Frean, M.1
-
15
-
-
0016102310
-
A projection pursuit algorithm for exploratory data analysis
-
J. H. Friedman and J. W. Tukey. A projection pursuit algorithm for exploratory data analysis. IEEE Transactions on Computers, C-23(9):881-889, 1974.
-
(1974)
IEEE Transactions on Computers
, vol.C-23
, Issue.9
, pp. 881-889
-
-
Friedman, J.H.1
Tukey, J.W.2
-
17
-
-
0003722376
-
-
Addison-Wesley, Reading, MA
-
D. Goldberg. Genetic algorithms in search, optimization, and machine learning. Addison-Wesley, Reading, MA, 1989.
-
(1989)
Genetic Algorithms in Search, Optimization, and Machine Learning
-
-
Goldberg, D.1
-
18
-
-
0004060921
-
-
PhD thesis, Department of Computer Science, University of Waikato, Hamilton, New Zealand
-
M. A. Hall. Correlation-based feature selection for machine learning. PhD thesis, Department of Computer Science, University of Waikato, Hamilton, New Zealand, 1999.
-
(1999)
Correlation-based Feature Selection for Machine Learning
-
-
Hall, M.A.1
-
20
-
-
17744402661
-
Feature subset selection by Bayesian networkbased optimization
-
I. Inza, P. Larranaga, R. Etxeberria, and B. Sierra. Feature subset selection by Bayesian networkbased optimization. Artificial Intelligence, 123(1-2):157-184, 2000.
-
(2000)
Artificial Intelligence
, vol.123
, Issue.1-2
, pp. 157-184
-
-
Inza, I.1
Larranaga, P.2
Etxeberria, R.3
Sierra, B.4
-
21
-
-
85099325734
-
Irrelevant features and the subset selection problem
-
New Brunswick, NJ, Morgan Kaufmann
-
G. H. John, R. Kohavi, and K. Pfleger. Irrelevant features and the subset selection problem. In Machine Learning: Proceedings of the Eleventh International Conference, pages 121-129, New Brunswick, NJ, 1994. Morgan Kaufmann.
-
(1994)
Machine Learning: Proceedings of the Eleventh International Conference
, pp. 121-129
-
-
John, G.H.1
Kohavi, R.2
Pfleger, K.3
-
23
-
-
0029306995
-
Statlog: Comparison of classification algorithms on large real-world problems
-
R. King, C. Feng, and A. Shutherland. Statlog: Comparison of classification algorithms on large real-world problems. Applied Artificial Intelligence, 9(3):259-287, 1995.
-
(1995)
Applied Artificial Intelligence
, vol.9
, Issue.3
, pp. 259-287
-
-
King, R.1
Feng, C.2
Shutherland, A.3
-
24
-
-
85146422424
-
A practical approach to feature selection
-
D. Sleeman and P. Edwards, editors, San Mateo, CA, Morgan Kaufmann
-
K. Kira and L. Rendell. A practical approach to feature selection. In D. Sleeman and P. Edwards, editors, Machine Learning: Proceedings of the Ninth International Conference, San Mateo, CA, 1992. Morgan Kaufmann.
-
(1992)
Machine Learning: Proceedings of the Ninth International Conference
-
-
Kira, K.1
Rendell, L.2
-
25
-
-
0008815681
-
Additive versus exponentiated gradient updates for linear prediction
-
J. Kivinen and M. K. Warmuth. Additive versus exponentiated gradient updates for linear prediction. Information and Computation, 132(1):1-64, 1997.
-
(1997)
Information and Computation
, vol.132
, Issue.1
, pp. 1-64
-
-
Kivinen, J.1
Warmuth, M.K.2
-
26
-
-
0003763626
-
-
PhD thesis, Department of Computer Science, Stanford University, Stanford, CA
-
R. Kohavi. Wrappers for performance enhancement and oblivious decision graphs. PhD thesis, Department of Computer Science, Stanford University, Stanford, CA, 1995.
-
(1995)
Wrappers for Performance Enhancement and Oblivious Decision Graphs
-
-
Kohavi, R.1
-
27
-
-
0031381525
-
Wrappers for feature subset selection
-
R. Kohavi and G. H. John. Wrappers for feature subset selection. Artificial Intelligence, 97(1-2):273-324, 1997.
-
(1997)
Artificial Intelligence
, vol.97
, Issue.1-2
, pp. 273-324
-
-
Kohavi, R.1
John, G.H.2
-
31
-
-
0000494466
-
Optimal brain damage
-
San Mateo, CA, Morgan Kaufmann
-
Y. Le Cun, J. Denker, and S. Solla. Optimal brain damage. In Advances in Neural Information Processing Systems 2, pages 598-605, San Mateo, CA, 1990. Morgan Kaufmann.
-
(1990)
Advances in Neural Information Processing Systems
, vol.2
, pp. 598-605
-
-
Le Cun, Y.1
Denker, J.2
Solla, S.3
-
32
-
-
34250091945
-
Learning quickly when irrelevant attributes abound: A new linear-threshold algorithm
-
N. Littlestone. Learning quickly when irrelevant attributes abound: A new linear-threshold algorithm. Machine Learning, 1988.
-
(1988)
Machine Learning
-
-
Littlestone, N.1
-
35
-
-
0001923944
-
Hoeffding races: Accelerating model selection search for classification and function approximation
-
Morgan Kaufmann
-
O. Maron and A. W. Moore. Hoeffding races: Accelerating model selection search for classification and function approximation. In Advances in Neural Information Processing Systems, volume 6. Morgan Kaufmann, 1994.
-
(1994)
Advances in Neural Information Processing Systems
, vol.6
-
-
Maron, O.1
Moore, A.W.2
-
38
-
-
0002787457
-
Architecture selection for neural networks: Application to corporate bond rating prediction
-
A. N. Refenes, editor, John Wiley and Sons
-
J. Moody and J. Utans. Architecture selection for neural networks: Application to corporate bond rating prediction. In A. N. Refenes, editor, Neural Networks in the Capital Markets. John Wiley and Sons, 1995.
-
(1995)
Neural Networks in the Capital Markets
-
-
Moody, J.1
Utans, J.2
-
39
-
-
33744584654
-
Induction of decision trees
-
J. R. Quinlan. Induction of decision trees. Machine Learning, 1(1):81-106, 1986.
-
(1986)
Machine Learning
, vol.1
, Issue.1
, pp. 81-106
-
-
Quinlan, J.R.1
-
41
-
-
11144273669
-
The perceptron: A probabilistic model for information storage and orginization in the brain
-
F. Rosenblatt. The perceptron: A probabilistic model for information storage and orginization in the brain. Psychological Review, 65:386-407, 1958.
-
(1958)
Psychological Review
, vol.65
, pp. 386-407
-
-
Rosenblatt, F.1
-
43
-
-
0000296415
-
Multivariate data analysis
-
L. Thurstone. Multivariate data analysis. Psychological Review, 38:406-427, 1931.
-
(1931)
Psychological Review
, vol.38
, pp. 406-427
-
-
Thurstone, L.1
-
46
-
-
0021518106
-
A theory of the learnable
-
L. G. Valiant. A theory of the learnable. Communications of the ACM, 27(11):1134-1142, 1984.
-
(1984)
Communications of the ACM
, vol.27
, Issue.11
, pp. 1134-1142
-
-
Valiant, L.G.1
-
48
-
-
0001001098
-
Feature selection for SVMs
-
MIT Press
-
J. Weston, S. Mukherjee, O. Chapelle, M. Pontil, T. Poggio, and V. Vapnik. Feature selection for SVMs. In Advances in Neural Information Processing Systems 13, pages 668-674. MIT Press, 2000.
-
(2000)
Advances in Neural Information Processing Systems
, vol.13
, pp. 668-674
-
-
Weston, J.1
Mukherjee, S.2
Chapelle, O.3
Pontil, M.4
Poggio, T.5
Vapnik, V.6
|