-
2
-
-
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):121-167 (1998).
-
(1998)
Data Mining and Knowledge Discovery
, vol.2
, Issue.2
, pp. 121-167
-
-
Burges, C.J.C.1
-
4
-
-
0033562880
-
New Methods for accurate prediction of protein secondary structure
-
Chandonia, J.M. and Karplus, M.: New Methods for accurate prediction of protein secondary structure. Proteins (1999) 35, 293-306.
-
(1999)
Proteins
, vol.35
, pp. 293-306
-
-
Chandonia, J.M.1
Karplus, M.2
-
5
-
-
0036893269
-
Transmembrane helix predictions revisited
-
Chen, C.P., Kernytsky, A. and Rost, B.: Transmembrane helix predictions revisited. Protein Science, vol. 11, (2002), pp. 2774-2791.
-
(2002)
Protein Science
, vol.11
, pp. 2774-2791
-
-
Chen, C.P.1
Kernytsky, A.2
Rost, B.3
-
6
-
-
0036776464
-
-
Cho, Y.H., Kim, J.K. and Kim, S.H.: A personalized recommender system based on web usage mining and decision tree induction. Expert Systems with Applications, 23, Issue 3, 1, (2002), 329-342.
-
Cho, Y.H., Kim, J.K. and Kim, S.H.: A personalized recommender system based on web usage mining and decision tree induction. Expert Systems with Applications, Volume 23, Issue 3, 1, (2002), 329-342.
-
-
-
-
7
-
-
0346331362
-
Decision Tree based on data envelopment analysis for effective technology commercialization
-
Sohn, S. Y. and Moon, T.H.: Decision Tree based on data envelopment analysis for effective technology commercialization. Expert Systems with Applications, Volume 26, Issue 2, (2004), 279-284.
-
(2004)
Expert Systems with Applications
, vol.26
, Issue.2
, pp. 279-284
-
-
Sohn, S.Y.1
Moon, T.H.2
-
8
-
-
0026458378
-
Amino Acid Substitution Matrices from Protein Blocks
-
Henikoff, S. and Henikoff, J.G.: Amino Acid Substitution Matrices from Protein Blocks. PNAS 89, 10915-10919 (1992).
-
(1992)
PNAS
, vol.89
, pp. 10915-10919
-
-
Henikoff, S.1
Henikoff, J.G.2
-
9
-
-
10644246923
-
Improved Protein Secondary Structure Prediction Using Support Vector Machine with a New Encoding Scheme and an Advanced Tertiary Classifier
-
Dec
-
Hu, H., Pan, Y., Harrison, R. and Tai, P. C.: Improved Protein Secondary Structure Prediction Using Support Vector Machine with a New Encoding Scheme and an Advanced Tertiary Classifier. IEEE Transactions on NanoBioscience, Vol. 3, No. 4, Dec. 2004, pp. 265-271.
-
(2004)
IEEE Transactions on NanoBioscience
, vol.3
, Issue.4
, pp. 265-271
-
-
Hu, H.1
Pan, Y.2
Harrison, R.3
Tai, P.C.4
-
10
-
-
0035957531
-
A Novel Method of Protein Secondary Structure Prediction with High Segment Overlap Measure: Support Vector Machine Approach
-
Hua, S. and Sun, Z.: A Novel Method of Protein Secondary Structure Prediction with High Segment Overlap Measure: Support Vector Machine Approach. J. Mol. Biol. (2001) 308: 397-407.
-
(2001)
J. Mol. Biol
, vol.308
, pp. 397-407
-
-
Hua, S.1
Sun, Z.2
-
11
-
-
17044421824
-
-
Joachims, T.: SVMlight. http://www.cs.cornell.edu/People/tj/svm_light/ (2002).
-
(2002)
SVMlight
-
-
Joachims, T.1
-
13
-
-
0034274591
-
A Comparison of Prediction Accuracy, Complexity, and Training Time of Thirty Tree Old and New Classification Algorithm
-
Sept
-
Lim, T.S., Loh, W.Y. and Shih, Y.S.: A Comparison of Prediction Accuracy, Complexity, and Training Time of Thirty Tree Old and New Classification Algorithm. Machine Learning, Vol. 40, no. 3, pp. 203-228, Sept. 2000.
-
(2000)
Machine Learning
, vol.40
, Issue.3
, pp. 203-228
-
-
Lim, T.S.1
Loh, W.Y.2
Shih, Y.S.3
-
16
-
-
0030643619
-
Clustering association rules
-
Lent, B., Swami, A. N. and Widom, J. Clustering association rules. In ICDE, 1997, pages 20-231.
-
(1997)
ICDE
, pp. 20-231
-
-
Lent, B.1
Swami, A.N.2
Widom, J.3
-
17
-
-
1542559402
-
-
B. Schoelkopf, K. Tsuda and J.-P. Vert, ed. MIT Press
-
Noble, W.S.: Kernel Methods in Computational Biology. B. Schoelkopf, K. Tsuda and J.-P. Vert, ed. MIT Press (2004) 71-92.
-
(2004)
Kernel Methods in Computational Biology
, pp. 71-92
-
-
Noble, W.S.1
-
18
-
-
10944251335
-
Rule-extraction from Support Vector Machines
-
Burges, ISBN 2-930307-02-1
-
Núñez, H., Angulo, C. and Catala, A.: Rule-extraction from Support Vector Machines. The European Symposium on Artifical Neural Networks, Burges, ISBN 2-930307-02-1, 2002, pp. 107-112.
-
(2002)
The European Symposium on Artifical Neural Networks
, pp. 107-112
-
-
Núñez, H.1
Angulo, C.2
Catala, A.3
-
19
-
-
0034776419
-
Automatic Rule Generation for protein Annotation with the C4.5 Data Mining Algorithm Applied on SWISS-PROT
-
Kretschmann, E., Fleischmann, W. and Apweiler, R.: Automatic Rule Generation for protein Annotation with the C4.5 Data Mining Algorithm Applied on SWISS-PROT. Bioinformatics, (2001), 17(10).
-
(2001)
Bioinformatics
, vol.17
, Issue.10
-
-
Kretschmann, E.1
Fleischmann, W.2
Apweiler, R.3
-
20
-
-
38049027502
-
-
Ruinlan, J.R.: C4.5:Programs for Machine Learning. San Mateo, Calif: Morgan Kaufmann, 1993.
-
Ruinlan, J.R.: C4.5:Programs for Machine Learning. San Mateo, Calif: Morgan Kaufmann, 1993.
-
-
-
-
21
-
-
0027291015
-
Prediction of protein Secondary Structure at Better than 70% Accuracy
-
Rost, B. and Sander, C.: Prediction of protein Secondary Structure at Better than 70% Accuracy. J. Mol. Biol. (1993) 232, 584-599.
-
(1993)
J. Mol. Biol
, vol.232
, pp. 584-599
-
-
Rost, B.1
Sander, C.2
-
23
-
-
1842455240
-
Bio-support Vector Machines for Computational Proteomics
-
Yang, Z.R. and Chou, K.: Bio-support Vector Machines for Computational Proteomics. Bioinformatics 20(5), 2004.
-
(2004)
Bioinformatics
, vol.20
, Issue.5
-
-
Yang, Z.R.1
Chou, K.2
-
24
-
-
27844568170
-
-
Sikder, A.R. and Zomaya, A.Y.: An overview of protein-folding techniques: Issues and perspectives, Int. J. Bioinformatics Research and Applications, 1, issure 1, pp. 121-143, 2005.
-
Sikder, A.R. and Zomaya, A.Y.: An "overview of protein-folding techniques: Issues and perspectives," Int. J. Bioinformatics Research and Applications, Vol. 1, issure 1, pp. 121-143, 2005.
-
-
-
-
25
-
-
27844596815
-
Transmembrane segments prediction and understanding using support vector machine and decision tree
-
He, J., Hu, H., Harrison, R., Tai, P.C. and Y. Pan, "Transmembrane segments prediction and understanding using support vector machine and decision tree," Expert Systems with Applications, Special Issue on Intelligent Bioinformatics Systems, vol. 30, pp. 64-72, 2006.
-
(2006)
Expert Systems with Applications
, vol.30
, pp. 64-72
-
-
He, J.1
Hu, H.2
Harrison, R.3
Tai, P.C.4
Pan, Y.5
-
26
-
-
0029484103
-
A Survey and Critique of Techniques for Extracting Rules from Trained Artificial Neural Networks
-
Andrews, R., Diederich, J. and Tickle, A.: A Survey and Critique of Techniques for Extracting Rules from Trained Artificial Neural Networks. Knowledge-Based Systems (1995), 8(6), pp. 373-389.
-
(1995)
Knowledge-Based Systems
, vol.8
, Issue.6
, pp. 373-389
-
-
Andrews, R.1
Diederich, J.2
Tickle, A.3
-
27
-
-
0032208720
-
The Truth will come to light: Directions and Challenges in Extracting the Knowledge Embedded within Trained Artificial Neural Networks
-
Tickle, A., Andrews, R., Mostefa, G. and Diederich, J.: The Truth will come to light: Directions and Challenges in Extracting the Knowledge Embedded within Trained Artificial Neural Networks. IEEE Transactions on Neural Networks, (1998), 9(6), pp. 1057-1068.
-
(1998)
IEEE Transactions on Neural Networks
, vol.9
, Issue.6
, pp. 1057-1068
-
-
Tickle, A.1
Andrews, R.2
Mostefa, G.3
Diederich, J.4
-
29
-
-
0036893269
-
Transmembrane helix predictions revisited
-
Chen, C.P., Kernytsky, A. and Rost, B.: Transmembrane helix predictions revisited. Protein Science, vol. 11, (2002), pp. 2774-2791.
-
(2002)
Protein Science
, vol.11
, pp. 2774-2791
-
-
Chen, C.P.1
Kernytsky, A.2
Rost, B.3
-
30
-
-
85142182105
-
-
Möller, S., Kriventseva, Apweiler, E.: V. and R.: A collection of well characterized integral membrane proteins. Bioinformatics, 16, (2000), pp. 1159-1160.
-
Möller, S., Kriventseva, Apweiler, E.: V. and R.: A collection of well characterized integral membrane proteins. Bioinformatics, vol. 16, (2000), pp. 1159-1160.
-
-
-
-
31
-
-
0033578684
-
Protein Secondary Structure Prediction Based on Position-specific Scoring Matrix
-
Jones, D. T.: "Protein Secondary Structure Prediction Based on Position-specific Scoring Matrix," J. Mol. Biol, vol. 292, (1999), pp. 195-202.
-
(1999)
J. Mol. Biol
, vol.292
, pp. 195-202
-
-
Jones, D.T.1
-
32
-
-
0034592911
-
Growing Decision Trees On Support-Less Association Rules
-
presented at, Boston, MA
-
Wang, K., Zhou, S. and Y. He, "Growing Decision Trees On Support-Less Association Rules," presented at Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'00), Boston, MA, 2000.
-
(2000)
Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'00)
-
-
Wang, K.1
Zhou, S.2
He, Y.3
-
33
-
-
38049078106
-
Understanding the Prediction of Transmembrane Proteins by Support Vector Machine using Association Rule Mining
-
presented at, Honolulu, Hawaii
-
Hu, H., Wang, H., Harrison, R., P.C. Tai, and Y. Pan, "Understanding the Prediction of Transmembrane Proteins by Support Vector Machine using Association Rule Mining," presented at IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB '07), Honolulu, Hawaii, 2007.
-
(2007)
IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB '07)
-
-
Hu, H.1
Wang, H.2
Harrison, R.3
Tai, P.C.4
Pan, Y.5
-
34
-
-
11344262990
-
CPAR: Classification based on Predictive Association Rules
-
presented at, San Fransisco, CA
-
Yin, X. and Han, J. "CPAR: Classification based on Predictive Association Rules," presented at SIAM Int. Conf. on Data Mining (SDM'03), San Fransisco, CA, 2003.
-
(2003)
SIAM Int. Conf. on Data Mining (SDM'03)
-
-
Yin, X.1
Han, J.2
-
40
-
-
38049045788
-
-
Quinlan, J. R. and Cameron-Jones, R. M.: FOIL: A Midterm report, presented at European Conference on Machine Learning (ECML-93), Vienna, Austria, 1993.
-
Quinlan, J. R. and Cameron-Jones, R. M.: FOIL: A Midterm report, presented at European Conference on Machine Learning (ECML-93), Vienna, Austria, 1993.
-
-
-
-
41
-
-
84948104699
-
Integrating classification and association rule mining
-
New York
-
Liu, B., Hsu, W. and Ma, Y.: Integrating classification and association rule mining, presented at The Fourth International Conference on Knowledge Discovery and Data Mining (KDD-98)′, New York, 1998.
-
(1998)
presented at The Fourth International Conference on Knowledge Discovery and Data Mining (KDD-98)′
-
-
Liu, B.1
Hsu, W.2
Ma, Y.3
-
42
-
-
0035812599
-
Energetics, stability, and prediction of transmembrane helices
-
Jayasinghe S, H. K. and White S.H.: Energetics, stability, and prediction of transmembrane helices., J. Mol. Biol., vol. 312, pp. 927-934, 2001.
-
(2001)
J. Mol. Biol
, vol.312
, pp. 927-934
-
-
Jayasinghe, S.H.K.1
White, S.H.2
-
43
-
-
2442574771
-
On Local Pruning of Association Rules Using Directed Hypergraphs
-
Chawla, S., Davis, J., Pandey, G. On Local Pruning of Association Rules Using Directed Hypergraphs. Proceedings of the 20th International Conference on Data Engineering, ICDE 2004: 832.
-
Proceedings of the 20th International Conference on Data Engineering
, vol.ICDE 2004
, pp. 832
-
-
Chawla, S.1
Davis, J.2
Pandey, G.3
-
44
-
-
0033355986
-
Distance based clustering of association rules
-
ASME Press, November
-
Gupta, G., Strehl, A. and Ghosh. J. Distance based clustering of association rules. In Intelligent Engineering Systems Through Artificial Neural Networks (Proceedings of ANNIE 1999), ASME Press, November, 1999., volume 9: Pages 759-764.
-
(1999)
Intelligent Engineering Systems Through Artificial Neural Networks (Proceedings of ANNIE
, vol.9
, pp. 759-764
-
-
Gupta, G.1
Strehl, A.2
Ghosh, J.3
-
45
-
-
84943262896
-
-
Lele, S., Golden, B., Ozga, K. and Wasil, E. Clustering Rules Using Empirical Similarity of Support Sets Lecture Notes In Computer Science; 2226 archive, Proceedings of the 4th International Conference on Discovery Science table of contents, 2001, Pages: 447-451.
-
Lele, S., Golden, B., Ozga, K. and Wasil, E. Clustering Rules Using Empirical Similarity of Support Sets Lecture Notes In Computer Science; Vol. 2226 archive, Proceedings of the 4th International Conference on Discovery Science table of contents, 2001, Pages: 447-451.
-
-
-
-
46
-
-
0002592397
-
Pruning and grouping discovered association rules
-
April
-
Toivonen, H., Klemettinen, M., Ronkainen, P. and Mannila. H. Pruning and grouping discovered association rules. In MLnet Workshop on Statistics, Machine Learning and Discovery in Databases, April, 1995: Pages 47-52.
-
(1995)
MLnet Workshop on Statistics, Machine Learning and Discovery in Databases
, pp. 47-52
-
-
Toivonen, H.1
Klemettinen, M.2
Ronkainen, P.3
Mannila, H.4
-
49
-
-
33644982752
-
Rule Generation for Protein Secondary Structure Prediction with Support Vector Machines and Decision Tree
-
March
-
He, J. Hu, H. Harrison, R., Tai, P.C. and Pan, Y.: Rule Generation for Protein Secondary Structure Prediction with Support Vector Machines and Decision Tree, IEEE Transactions on NanoBioscience, Vol. 5, No. 1, March 2006, pp. 46-53.
-
(2006)
IEEE Transactions on NanoBioscience
, vol.5
, Issue.1
, pp. 46-53
-
-
He, J.1
Hu, H.2
Harrison, R.3
Tai, P.C.4
Pan, Y.5
-
50
-
-
33749059974
-
Rule Clustering and Super rule Generation for Transmembrane Segments Prediction
-
August 8-11, Califormia, USA, Poster, pp
-
He, J. Hu, H. Harrison, R., Tai, P.C., Dong, Y. and Pan, Y: Rule Clustering and Super rule Generation for Transmembrane Segments Prediction, Proceedings of IEEE Computational Systems Bioinformatics Conference (CSB 2005), August 8-11, 2005, Califormia, USA, Poster, pp. 224-227.
-
(2005)
Proceedings of IEEE Computational Systems Bioinformatics Conference (CSB
, pp. 224-227
-
-
He, J.1
Hu, H.2
Harrison, R.3
Tai, P.C.4
Dong, Y.5
Pan, Y.6
-
51
-
-
1642327509
-
Rule extraction:uSing neural networks or for neural networks?
-
Zhou, Z.-H. Rule extraction:uSing neural networks or for neural networks? Journal of Computer Science and Technology, 2004, 19(2), 249-253.
-
(2004)
Journal of Computer Science and Technology
, vol.19
, Issue.2
, pp. 249-253
-
-
Zhou, Z.-H.1
|