Sparse Zero-Sum Games as Stable Functional Feature Selection

作者：Sokolovska Nataliya^*; Teytaud Olivier; Rizkalla Salwa; Consortium MicroObese; Clement Karine; Zucker Jean Daniel

来源：PLos One, 2015, 10(9): e0134683.

DOI：10.1371/journal.pone.0134683

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.

• 出版日期2015-9-1
• 单位INRIA