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Association rules identify patterns in data sets from "summary" of Data Science for Business by Foster Provost,Tom Fawcett
Association rules are a powerful tool in data mining that allow us to uncover interesting patterns in large data sets. These rules help us identify relationships between different variables based on their co-occurrence within the data. By analyzing these patterns, we can gain valuable insights into the underlying structure of the data and make informed decisions. The process of discovering association rules involves examining the frequency of itemsets in the data and determining the level of support and confidence for each rule. Support measures how frequently a particular itemset appears in the data, while confidence measures the likelihood that one item will appear given the presence of another item. By setting appropriate thresholds for support and confidence, we can filter out spurious rules and focus on the most meaningful associations. Association rules are particularly useful in market basket ...
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