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Discovering Reliable Correlations in Categorical Data
2019
2019 IEEE International Conference on Data Mining (ICDM)
In many scientific tasks we are interested in discovering whether there exist any correlations in our data. This raises many questions, such as how to reliably and interpretably measure correlation between a multivariate set of attributes, how to do so without having to make assumptions on distribution of the data or the type of correlation, and, how to efficiently discover the topmost reliably correlated attribute sets from data. In this paper we answer these questions for discovery tasks in
doi:10.1109/icdm.2019.00156
dblp:conf/icdm/MandrosBV19
fatcat:2kwhrtex4vbdxp2c6zgubozl2q