Testing the significance of attribute interactions

147 citations recorded by the source corpus.

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Interpreting Classifiers through Attribute Interactions in Datasets (2017, neutral): “Tatti (2011) ordered attributes according to their dependencies while Jakulin & Bratko (2003) quantiﬁed the degree of attribute interaction and Jakulin & Bratko (2004) factorised the joint data distribution and presented a method for signiﬁcance testing of attribute interactions.”
Nomograms for visualizing support vector machines (2005, methodology): “First, interaction analysis [14] is a heuris-”
Searching for interacting features in subset selection (2009, unknown): “An intrinsic character of feature interaction is its irreducibility [26], i.”
Finding Statistically Significant Attribute Interactions (2016, methodology): “[ 10] proposed a method for quantifying the degree of interaction and [11] consider factorising the joint data distribution and presented a method for testing the significance of the found attribute interactions (experiments limited to two and three-way interactions).”
A Survey on Evolutionary Computation Approaches to Feature Selection (2016, background): “Ignoring interactions between features results in subsets with redundancy and lack of complimentary features [2], [241], which in turn cannot achieve optimal classification performance in most domains of interest.”