Exploiting statistically significant dependent rules for associative classification
Jundong Li; Osmar R. Zaı̈ane · 2017 · Intelligent Data Analysis
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract (excerpt)
Established associative classification algorithms have shown to be very effective in handling categorical data such as text data. The learned model is a set of rules that are easy to understand and can be edited. However, they still suffer…
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WASTE indexes this work — it does not host or republish it. Failure-type classification is automated and approximate.
Metadata source: OpenAlex · DOI 10.3233/ida-163141