Valid interpretation of feature relevance for linear data mappings

Frenay B, Hofmann D, Schulz A, Biehl M, Hammer B (2014)
In: 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM). Institute of Electrical & Electronics Engineers (IEEE): 149-156.

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IEEE Symposium on Computational Intelligence and Data Mining (CIDM)
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2014.12.09 – 2014.12.12
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Frenay B, Hofmann D, Schulz A, Biehl M, Hammer B. Valid interpretation of feature relevance for linear data mappings. In: 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM). Institute of Electrical & Electronics Engineers (IEEE); 2014: 149-156.
Frenay, B., Hofmann, D., Schulz, A., Biehl, M., & Hammer, B. (2014). Valid interpretation of feature relevance for linear data mappings. 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM), 149-156.
Frenay, B., Hofmann, D., Schulz, A., Biehl, M., and Hammer, B. (2014). “Valid interpretation of feature relevance for linear data mappings” in 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM) (Institute of Electrical & Electronics Engineers (IEEE), 149-156.
Frenay, B., et al., 2014. Valid interpretation of feature relevance for linear data mappings. In 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM). Institute of Electrical & Electronics Engineers (IEEE), pp. 149-156.
B. Frenay, et al., “Valid interpretation of feature relevance for linear data mappings”, 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM), Institute of Electrical & Electronics Engineers (IEEE), 2014, pp.149-156.
Frenay, B., Hofmann, D., Schulz, A., Biehl, M., Hammer, B.: Valid interpretation of feature relevance for linear data mappings. 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM). p. 149-156. Institute of Electrical & Electronics Engineers (IEEE) (2014).
Frenay, Benoit, Hofmann, Daniela, Schulz, Alexander, Biehl, Michael, and Hammer, Barbara. “Valid interpretation of feature relevance for linear data mappings”. 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM). Institute of Electrical & Electronics Engineers (IEEE), 2014. 149-156.
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