Unsupervised Features Ranking via Coalitional Game Theory for Categorical Data. (arXiv:2205.09060v1 [cs.LG])

Not all real-world data are labeled, and when labels are not available, it is
often costly to obtain them. Moreover, as many algorithms suffer from the curse
of dimensionality, reducing the features in the data to a smaller set is often
of great utility. Unsupervised feature selection aims to reduce the number of
features, often using feature importance scores to quantify the relevancy of
single features to the task at hand. These scores can be based only on the
distribution …

arxiv data features game game theory ranking theory unsupervised