LS-SVM based spectral clustering and regression for predicting maintenance of industrial machines

Author:

Langone Rocco,Alzate Carlos,De Ketelaere Bart,Vlasselaer Jonas,Meert Wannes,Suykens Johan A.K.

Funder

European Research Council

Flemish Government: FWO

SBO POM

iMinds Medical Information Technologies SBO 2014 Belgian Federal Science Policy Office: IUAP P7/19

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering

Reference35 articles.

1. Alzate, C., Suykens, J.A.K., 2010a. Highly sparse kernel spectral clustering with predictive out-of-sample extensions. In: Proceedings of the 18th European Symposium on Artificial Neural Networks (ESANN 2010), pp. 235–240.

2. Multiway spectral clustering with out-of-sample extensions through weighted kernel PCA;Alzate;IEEE Trans. Pattern Anal. Mach. Intell.,2010

3. Probabilistic d-clustering;Ben-Israel;J. Classif.,2008

4. A survey of clustering data mining techniques;Berkhin;Grouping Multidimens. Data,2006

5. Bey-Temsamani, A., Engels, M., Motten, A., Vandenplas, S., Ompusunggu, A.P., 2009. A practical approach to combine data mining and prognostics for improved predictive maintenance. In: Proceedings of the Third International Workshop on Data Mining Case Studies (DMCS), pp. 36–43.

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