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Consensus Group Stable Feature Selection

Consensus Group Stable Feature Selection

This video was recorded at 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), Paris 2009. Stability is an important yet under-addressed issue in feature selection from high-dimensional and small sample data. In this paper, we show that stability of feature selection has a strong dependency on sample size. We propose a novel framework for stable feature selection which first identifies consensus feature groups from subsampling of training samples, and then performs feature selection by treating each consensus feature group as a single entity. Experiments on both synthetic and real-world data sets show that an algorithm developed under this framework is effective at alleviating the problem of small sample size and leads to more stable feature selection... Show More

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