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Everything about Associative classifier

Machine learning model type

An associative classifier (AC) is a kind of supervised learning model that uses association rules to assign a target value. The term associative classification was coined by Bing Liu et al., in which the authors defined a model made of rules "whose right-hand side are restricted to the classification class attribute". Wikipedia →

🧭 Start here: a 6-step reading path

  1. Read the overview: Associative classifierA 5-minute orientation
  2. Skim a recent paper: PaSOFuAC: Particle Swarm Optimization Based Fuzzy Associative Classifier for Detecting Phishing WebsitesInfluential work since 2022
  3. Pick up a classic book: SLACCThe most-reprinted book on the subject
  4. Read the landmark paper: One-Hot Vector Hybrid Associative Classifier for Medical Data ClassificationCited 46 times
  5. Go sideways: Bing Liu (computer scientist)A closely related topic
  6. Go sideways: Association rule learningA closely related topic

📖 Definitions

No dictionary entry for this exact phrase.

🗂️ The subject at a glance

  1. Model
  2. Metrics
  3. Implementations

🏆 Landmark papers (most cited)

🆕 Influential since 2022

📚 Books worth reading

Ranked by number of editions on Open Library, a rough measure of how lasting a book is.

🔗 Related topics