Sparse Zero-Sum Games as Stable Functional Feature Selection.
In large-scale systems biology applications, features are structured in hidden functional categories whose predictive power is identical. Feature selection, therefore, can lead not only to a problem with a reduced dimensionality, but also reveal some knowledge on functional classes of variables. In this contribution, we propose a framework based on a sparse zero-sum game which performs a stable functional feature selection. In particular, the approach is based on feature subsets ranking by a thresholding stochastic bandit. We provide a theoretical analysis of the introduced algorithm. We illustrate by experiments on both synthetic and real complex data that the proposed method is competitive from the predictive and stability viewpoints.
Institute of Cardiometabolism and Nutrition, ICAN, Assistance Publique Hôpitaux de Paris, Pitié-Salpêtrière Hospital, Paris, France; Sorbonne Universités, UPMC University Paris 6, UMR_S 1166, ICAN, NutriOmics Team, Paris, France; INSERM, UMR S U1166, NutriOmics Team, Paris, France.
Nataliya
N
Sokolovska
LRI, University Paris 11, INRIA Saclay, Orsay, France.
Olivier
O
Teytaud
Institute of Cardiometabolism and Nutrition, ICAN, Assistance Publique Hôpitaux de Paris, Pitié-Salpêtrière Hospital, Paris, France; Sorbonne Universités, UPMC University Paris 6, UMR_S 1166, ICAN, NutriOmics Team, Paris, France; INSERM, UMR S U1166, NutriOmics Team, Paris, France.
Salwa
S
Rizkalla
Institute of Cardiometabolism and Nutrition, ICAN, Assistance Publique Hôpitaux de Paris, Pitié-Salpêtrière Hospital, Paris, France; Sorbonne Universités, UPMC University Paris 6, UMR_S 1166, ICAN, NutriOmics Team, Paris, France; INSERM, UMR S U1166, NutriOmics Team, Paris, France.
Karine
K
Clément
Institute of Cardiometabolism and Nutrition, ICAN, Assistance Publique Hôpitaux de Paris, Pitié-Salpêtrière Hospital, Paris, France; Sorbonne Universités, UPMC University Paris 6, UMR_S 1166, ICAN, NutriOmics Team, Paris, France; INSERM, UMR S U1166, NutriOmics Team, Paris, France; Research Institute for Development, UMI UMMISCO, Bondy, France.
Jean-Daniel
JD
Zucker
D000465:Algorithms; D005716:Game Theory; D005717:Games, Experimental; D020869:Gene Expression Profiling / Q000379:methods; D006801:Humans; D056186:Metagenomics / Q000379:methods; D015233:Models, Statistical; D013269:Stochastic Processes; D049490:Systems Biology / Q000379:methods