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Volumn 4243 LNCS, Issue , 2006, Pages 197-206

Data mining with parallel support vector machines for classification

Author keywords

Classification; Data mining; Parallelization; Support vector machine

Indexed keywords

CLASSIFICATION (OF INFORMATION); LEARNING SYSTEMS; MATHEMATICAL MODELS; PARALLEL PROCESSING SYSTEMS; PARAMETER ESTIMATION;

EID: 33751367993     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11890393_21     Document Type: Conference Paper
Times cited : (7)

References (28)
  • 1
    • 22944471123 scopus 로고    scopus 로고
    • Cytochrome p450 classification of drugs with support vector machines implementing the nearest point algorithm
    • López, J.A., Benfenati, E., Dubitzky, W., eds.: Knowledge Exploration in Life Science Informatics, International Symposium, KELSI 2004, Milan, Italy. Springer
    • Kless, A., Eitrich, T.: Cytochrome p450 classification of drugs with support vector machines implementing the nearest point algorithm. In López, J.A., Benfenati, E., Dubitzky, W., eds.: Knowledge Exploration in Life Science Informatics, International Symposium, KELSI 2004, Milan, Italy. Volume 3303 of Lecture Notes in Computer Science., Springer (2004) 191-205
    • (2004) Lecture Notes in Computer Science , vol.3303 , pp. 191-205
    • Kless, A.1    Eitrich, T.2
  • 3
    • 44749083335 scopus 로고    scopus 로고
    • Discovering compact and highly discriminative features or feature combinations of drug activities using support vector machines
    • 11-14 August 2003, Stanford, CA, USA, IEEE Computer Society
    • Yu, H., Yang, J., Wang, W., Han, J.: Discovering compact and highly discriminative features or feature combinations of drug activities using support vector machines. In: 2nd IEEE Computer Society Bioinformatics Conference (CSB 2003), 11-14 August 2003, Stanford, CA, USA, IEEE Computer Society (2003) 220-228
    • (2003) 2nd IEEE Computer Society Bioinformatics Conference (CSB 2003) , pp. 220-228
    • Yu, H.1    Yang, J.2    Wang, W.3    Han, J.4
  • 5
    • 84949510307 scopus 로고    scopus 로고
    • A data-clustering algorithm on distributed memory multiprocessors
    • Large-Scale Parallel Data Mining
    • Dhillon, I.S., Modha, D.S.: A data-clustering algorithm on distributed memory multiprocessors. In: Large-Scale Parallel Data Mining, Lecture Notes in Artificial Intelligence. (2000) 245-260
    • (2000) Lecture Notes in Artificial Intelligence , pp. 245-260
    • Dhillon, I.S.1    Modha, D.S.2
  • 6
    • 17444402472 scopus 로고    scopus 로고
    • Shared memory parallelization of data mining algorithms: Techniques, programming interface, and performance
    • Jin, R., Yang, G., Agrawal, G.: Shared memory parallelization of data mining algorithms: techniques, programming interface, and performance. IEEE Transactions on Knowledge and Data Engineering 17 (2005) 71-89
    • (2005) IEEE Transactions on Knowledge and Data Engineering , vol.17 , pp. 71-89
    • Jin, R.1    Yang, G.2    Agrawal, G.3
  • 8
    • 0036505670 scopus 로고    scopus 로고
    • A comparison of methods for multi-class support vector machines
    • Hsu, C., Lin, C.: A comparison of methods for multi-class support vector machines. IEEE Transactions on Neural Networks 13 (2002) 415-425
    • (2002) IEEE Transactions on Neural Networks , vol.13 , pp. 415-425
    • Hsu, C.1    Lin, C.2
  • 12
    • 27144489164 scopus 로고    scopus 로고
    • 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 (1998) 121-167
    • (1998) Data Mining and Knowledge Discovery , vol.2 , pp. 121-167
    • Burges, C.J.C.1
  • 13
    • 0036158552 scopus 로고    scopus 로고
    • A simple decomposition method for support vector machines
    • Hsu, C.W., Lin, C.J.: A simple decomposition method for support vector machines. Machine Learning 46 (2002) 291-314
    • (2002) Machine Learning , vol.46 , pp. 291-314
    • Hsu, C.W.1    Lin, C.J.2
  • 15
    • 33749988574 scopus 로고    scopus 로고
    • Efficient optimization of support vector machine learning parameters for unbalanced datasets
    • in press
    • Eitrich, T., Lang, B.: Efficient optimization of support vector machine learning parameters for unbalanced datasets. Journal of Computational and Applied Mathematics (2005) in press.
    • (2005) Journal of Computational and Applied Mathematics
    • Eitrich, T.1    Lang, B.2
  • 16
    • 12444278992 scopus 로고    scopus 로고
    • Gradient projection methods for quadratic programs and applications in training support vector machines
    • Serafini, T., Zanghirati, G., Zanni, L.: Gradient projection methods for quadratic programs and applications in training support vector machines. Optimization Methods and Software 20 (2005) 353-378
    • (2005) Optimization Methods and Software , vol.20 , pp. 353-378
    • Serafini, T.1    Zanghirati, G.2    Zanni, L.3
  • 17
    • 0000859664 scopus 로고
    • An algorithm for a singly constrained class of quadratic programs subject to upper and lower bounds
    • Pardalos, P.M., Kovoor, N.: An algorithm for a singly constrained class of quadratic programs subject to upper and lower bounds. Mathematical Programming 46 (1990) 321-328
    • (1990) Mathematical Programming , vol.46 , pp. 321-328
    • Pardalos, P.M.1    Kovoor, N.2
  • 18
    • 0036583160 scopus 로고    scopus 로고
    • A parallel mixture of SVMs for very large scale problems
    • Collobert, R., Bengio, S., Bengio, Y.: A parallel mixture of SVMs for very large scale problems. Neural Computation 14 (2002) 1105-1114
    • (2002) Neural Computation , vol.14 , pp. 1105-1114
    • Collobert, R.1    Bengio, S.2    Bengio, Y.3
  • 23
    • 32144463893 scopus 로고    scopus 로고
    • Parallel tuning of support vector machine learning parameters for large and unbalanced data sets
    • Berthold, M.R., Glen, R., Diederichs, K., Kohlbacher, O., Fischer, I., eds.: Computational Life Sciences, First International Symposium, CompLife 2005, Konstanz, Germany. Springer
    • Eitrich, T., Lang, B.: Parallel tuning of support vector machine learning parameters for large and unbalanced data sets. In Berthold, M.R., Glen, R., Diederichs, K., Kohlbacher, O., Fischer, I., eds.: Computational Life Sciences, First International Symposium, CompLife 2005, Konstanz, Germany. Volume 3695 of Lecture Notes in Computer Science., Springer (2005) 253-264
    • (2005) Lecture Notes in Computer Science. , vol.3695 , pp. 253-264
    • Eitrich, T.1    Lang, B.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.