Understanding the Crucial Role of Attribute Interaction in Data Mining

By Alex Alves Freitas. 2001

173 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Information Systems, Signal Processing

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Citations in the corpus

Interpreting Classifiers through Attribute Interactions in Datasets (2017, background): “For a review on attribute interactions in data mining see, e.g., Freitas (2001).”
The Ubiquitous Nature of Epistasis in Determining Susceptibility to Common Human Diseases (2003, background): “Detecting interactions among variables is a well-known challenge in statistics and data mining [Freitas, 2001].”
Data mining with an ant colony optimization algorithm (2002, background): “For a general discussion about why evolutionary algorithms tend to cope better with attribute interactions than greedy localsearch-based decision tree and rule induction algorithms, the reader is referred to [8] and [14] .”
Multifactor dimensionality reduction software for detecting gene-gene and gene-environment interactions (2003, background): “Detecting interactions among variables is a well-known problem in data mining (Freitas, 2001) and an increasingly recognized problem in human genetics (Templeton, 2000; Moore and Williams, 2002).”
A novel evolutionary data mining algorithm with applications to churn prediction (2003, background): “Recently, the use of GAs for rule discovery in the application of data mining has been studied in [9], [12], [15], [26].”
Class Noise vs. Attribute Noise: A Quantitative Study (2003, background): “The attributes are assumed to have weak interactions (Freitas 2001) with each other, so the learning algorithms likely ignore these interactions and consider each attribute independently to induce the classifier.”
A peek into the black box: exploring classifiers by randomization (2014, background): “It should be noted that the task bears a close resemblance to that of finding attribute interactions when analyzing datasets in general, see e.g., Freitas (2001), Jakulin et al. (2003), Zhao and Liu (2007), Zhao and Liu (2009), Chanda et al. (2009).”