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Data Analysis and Confidence based on SVM Density Estimation.

, и . IJCNN, стр. 1818-1824. IEEE, (2006)

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Michael Jordaan

Michael Jordaan

Michael Jordaan

Michael Jordaan

Elsa Güllich

 

Другие публикации лиц с тем же именем

Evaluation of Performance Measures for SVR Hyperparameter Selection., , и . IJCNN, стр. 637-642. IEEE, (2007)Empirical Models with Self-Assessment Capabilities for On-Line Industrial Applications., , , , , и . IEEE Congress on Evolutionary Computation, стр. 3106-3113. IEEE, (2006)Confidence of SVM Predictions using a Strangeness Measure., и . IJCNN, стр. 1239-1246. IEEE, (2006)Biomass Inferential Sensor Based on Ensemble of Models Generated by Genetic Programming., , , , , , и . GECCO (2), том 3103 из Lecture Notes in Computer Science, стр. 1078-1089. Springer, (2004)Competitive advantages of evolutionary computation for industrial applications., , , , , и . Congress on Evolutionary Computation, стр. 166-173. IEEE, (2005)Data Analysis and Confidence based on SVM Density Estimation., и . IJCNN, стр. 1818-1824. IEEE, (2006)Robust Inferential Sensors Based on Ensemble of Predictors Generated by Genetic Programming., , , и . PPSN, том 3242 из Lecture Notes in Computer Science, стр. 522-531. Springer, (2004)Novel Approach to Develop Rheological Structure-Property Relationships Using Genetic Programming., , и . PPSN, том 4193 из Lecture Notes in Computer Science, стр. 322-331. Springer, (2006)Discovering novelty in spatio/temporal data using one-class support vector machines., , и . IJCNN, стр. 2956-2963. IEEE Computer Society, (2009)Robust soft sensors based on integration of genetic programming, analytical neural networks, and support vector machines., , , и . IEEE Congress on Evolutionary Computation, стр. 896-901. IEEE, (2002)