Discovering feature relevancy and dependency by kernel-guided probabilistic model-building evolution

Author:

Rodriguez Nestor,Rojas–Galeano Sergio

Publisher

Springer Science and Business Media LLC

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Genetics,Molecular Biology,Biochemistry

Reference55 articles.

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3. Aldehim G, Wang W. Determining appropriate approaches for using data in feature selection. Intl J Mach Learn Cybernet. 2016; Online first:1–14.

4. Bolón-Canedo V, Sánchez-Maroño N, Alonso-Betanzos A, Benítez JM, Herrera F. A review of microarray datasets and applied feature selection methods. Inf Sci. 2014; 282(0):111–35.

5. Szymczak S, Holzinger E, Dasgupta A, Malley JD, Molloy AM, Mills JL, Brody LC, Stambolian D, Bailey-Wilson JE. r2vim: A new variable selection method for random forests in genome-wide association studies. BioData Mining. 2016; 9(1):1–15.

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