Abstract
The curse of dimensionality is one of the well known issues in Biological data bases. A possible solution to avoid this issue is to use feature selection approach. Filter feature selection are well know feature selection methods that selects the most significant features and discards the rest according to their significance level. In general The set of eliminated features may hide some useful information that may be valuable in further studies. Hence, this paper present a new approach for filter feature selection that uses redundant features to create new instances and avoid the curse of dimensionality.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bellman, R.: Processus Adaptive Control: A Guided Tour. Princeton University Press, Princeton (1961)
Guerif, S.: Rduction de dimension en apprentissage numrique non supervise. Ph.D. thesis, Universit Paris 13 (2006)
Salvador, G., Julin, L., Francisco, H.: Data preprocessing in Data Mining. In: Kacprzyk, J., (ed.) Polish Academy of Sciences. Springer, Poland, Warsaw (2015)
Pomeroy, S.L., Tamayo, P., Gaasenbeek, M., Sturla, L.M., Angelo, M., McLaughlin, M.E., Kim, J.Y.H., Goumnerova, L.C., Black, P.M., Lau, C., Allen, J.C., Zagzag, D., Olson, J.M., Curran, T., Wetmore, C., Biegel, J.A., Poggio, T., Mukherjee, S., Rifkin, R., Califano, A., Stolovitzky, G., Louis, D.N., Mesirov, J.P., Lander, E.S., Golub, T.R.: Prediction of central nervous system embryonal tumour outcome based on gene expression. Nat. 415(6870), 436–442 (2002)
Golub, T.R., Slonim, D.K., Tamayo, P., Huard, C., Gaasenbeek, M., Mesirov, J.P., Coller, H., Loh, M.L., Downing, J.R., Caligiuri, M.A., Bloomfield, C.D.: Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Sci. 286, 531–537 (1999)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Mouelhi, E., Bouaguel, W., Bel Mufti, G. (2015). A Redundancy Study for Feature Selection in Biological Data. In: Prasath, R., Vuppala, A., Kathirvalavakumar, T. (eds) Mining Intelligence and Knowledge Exploration. MIKE 2015. Lecture Notes in Computer Science(), vol 9468. Springer, Cham. https://doi.org/10.1007/978-3-319-26832-3_3
Download citation
DOI: https://doi.org/10.1007/978-3-319-26832-3_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-26831-6
Online ISBN: 978-3-319-26832-3
eBook Packages: Computer ScienceComputer Science (R0)