Mierswa RITTHOFF, O. and KLINKENBERG, R. and FISCHER, S. and MIERSWA, I. (2002): A Hybrid Approach to Feature Selection and Generation Using an Evolutionary Algorithm. Technical report CI-127/02, University of Dortmund. R UPING, S. (2000): mySVM - Manual. University of Dortmund. Home/Search Document Details and Download
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Support Vector Machines and Learning about Time - Rüping, Morik (2003) (Correct)
.... with support vector machines (SVMs, 24] Support vector machines have been applied to very di erent kinds of learning problems, for example to time series prediction by Mukherjee et al. in [17] and by M uller et al. in [18] A regression problem for time series has been solved with SVMs in [20], where certain coecients of chemical components have been predicted from chromatography time series. Chang et al. 3] have presented an approach for time series segmentation with SVMs, which consists of simultaneously learning multiple SVMs models for one time series. All of these applications ....
.... a high dimensional, noisy classi cation problem on multivariate time series it was found in [16] that the best representation was to ignore time dependencies completely and make a non temporal classi cation based on the last obeservation only. In the eld of chromatography, Rittho et al. [20] solved the problem of predicting certain chemical coecients based on the chromatographical analysis of a substance (which is a time series of intensities of chemical components) by describing the time series by chosen analytical properties, e.g. the location of its maximum. That is, they did not ....
Oliver Rittho , Ralf Klinkenberg, Simon Fischer, and Ingo Mierswa. A hybrid approach to feature selection and generation using an evolutionary algorithm. In John A. Bullinaria, editor, Proceedings of the 2002.
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Mierswa RITTHOFF, O. and KLINKENBERG, R. and FISCHER, S. and MIERSWA, I. (2002): A Hybrid Approach to Feature Selection and Generation Using an Evolutionary Algorithm. Technical report CI-127/02, University of Dortmund. R UPING, S. (2000): mySVM - Manual. University of Dortmund.
Automatic Feature Extraction from Large Time Series - Mierswa (2004) Self-citation (Mierswa) (Correct)
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Mierswa RITTHOFF, O. and KLINKENBERG, R. and FISCHER, S. and MIERSWA, I. (2002): A Hybrid Approach to Feature Selection and Generation Using an Evolutionary Algorithm. Technical report CI-127/02, University of Dortmund. R UPING, S. (2000): mySVM - Manual. University of Dortmund.
Support Vector Machines And Learning About Time - Stefan Uping And (2003) (Correct)
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Oliver Ritthoff, Ralf Klinkenberg, Simon Fischer, and Ingo Mierswa, "A hybrid approach to feature selection and generation using an evolutionary algorithm," in Proc. of the UKCI-02, J. Bullinaria, Ed., Birmingham, UK, 2002, pp. 147--154, Univ. of Birmingham.
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Oliver Ritthoff, Ralf Klinkenberg, Simon Fischer, and Ingo Mierswa. A hybrid approach to feature selection and generation using an evolutionary algorithm. Technical Report CI-127/02, Collaborative Research Center 531, University of Dortmund, Germany, 2002.
Constructive Induction Using Non-algebraic Feature Representation - Shafti, Perez (Correct)
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O. Ritthoff, R. Klinkenberg, S. Fischer & I. Mierswa, A hybrid approach to feature selection and generation using an evolutionary algorithm, Proc. 2002.
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