T. Van Gestel, J.A.K. Suykens, D.-E. Baestaens, A. Lambrechts, G. Lanckriet, B. Vandaele, B. De Moor, J. Vandewalle, Financial time series prediction using least squares support vector machines within the evidence framework, IEEE Transactions on Neural Networks 12 (4) (2001) 809 -- 821. Home/Search Document Details and Download
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T. Van Gestel, J. Suykens, D. Baestaens, A. Lambrechts, G. Lanckriet, B. Vandaele, B. De Moor, J. Vandewalle, "Financial Time Series Prediction using Least Squares Support Vector Machines within the Evidence Framework," IEEE Transactions on Neural Networks, Special Issue on Neural Networks in Financial Engineering, vol. 12, no. 4, Jul. 2001, pp. 809-821.
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Van Gestel T, Suykens JAK, Baestaens D-E, Lamrechts A, Lanckriet G, Vandaele B, De Moor B, Vandewalle J. Financial time series prediction using least squares support vector machines within the evidence framework, IEEE Trans Neural Netw (Special Issue on Financial Engineering) 2001;12(4):809821.
Weighted Least Squares Support Vector Machines.. - Suykens, De.. (4 citations) Self-citation (Suykens Vandewalle) (Correct)
....are related to the SSE cost function which means that (up to a certain extent) one can still correct for wrong assumptions by an appropriate choice of the hyperparameters. These can be determined in several possible ways such as crossvalidation, bootstrapping, VC bounds, Bayesian inference etc. [4, 34]. We show in this paper how one can apply weighted least squares in order to produce a more robust estimate. This is done by rst applying an (unweighted) LS SVM and, in a second stage, associate weighting values to the error variables based upon the resulting error variables from the rst stage. ....
Van Gestel T., Suykens J.A.K., Baestaens D., Lambrechts A., Lanckriet G., Vandaele B., De Moor B., Vandewalle J., \Financial time series prediction using least squares support vector machines within the evidence framework," IEEE Transactions on Neural Networks (special issue on Neural Networks in Financial Engineering), in press.
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T. Van Gestel, J.A.K. Suykens, D.-E. Baestaens, A. Lambrechts, G. Lanckriet, B. Vandaele, B. De Moor, J. Vandewalle, Financial time series prediction using least squares support vector machines within the evidence framework, IEEE Transactions on Neural Networks 12 (4) (2001) 809 -- 821.
Efficient Evaluation of Composite Correlations - For Streaming Time (Correct)
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T. V. Gestel, J. Suykens, D.-E. Baestaens, A. Lambrechts, G. Lanckriet, B. Vandaele, D. B. Moor, and J. Vandewalle. Financial time series prediction using least squares support vector machines within the evidence framework. IEEE Transactions on Neural Networks, 12(4):809--821, 2001.
Ecient Evaluation of Composite Correlations - For Streaming Time (Correct)
No context found.
T. V. Gestel, J. Suykens, D.-E. Baestaens, A. Lambrechts, G. Lanckriet, B. Vandaele, D. B. Moor, and J. Vandewalle. Financial time series prediction using least squares support vector machines within the evidence framework. IEEE Transactions on Neural Networks, 12#4#:809#821, 2001.
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