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stat.ML2017★ 31 cited
Interpreting Classifiers through Attribute Interactions in Datasets
Andreas Henelius, Kai Puolamäki, Antti Ukkonen
In this work we present the novel ASTRID method for investigating which attribute interactions classifiers exploit when making predictions. Attribute interactions in classification…
stat.ML2009★ 6 cited
Multiple Hypothesis Testing in Pattern Discovery
Sami Hanhijärvi, Kai Puolamäki, Gemma C. Garriga
The problem of multiple hypothesis testing arises when there are more than one hypothesis to be tested simultaneously for statistical significance. This is a very common situation…