[PDF] association analysis python

  • What is association analysis?

    Association analysis is the task of finding interesting relationships in large datasets. These interesting relationships can take two forms: frequent item sets or association rules.

  • How do you interpret association rules in Python?

    An association rule is a statement of the form "if item A is present in a transaction, then item B is also likely to be present". The strength of the association is measured using the confidence of the rule, which is the probability that item B is present given that item A is present.

  • How do you analyze association rules?

    The following measures are commonly used to evaluate association rules:

    1Support: Rules with high support are more significant as they occur more frequently in the dataset.2Confidence: Rules with high confidence are more reliable, as they have a higher probability of being true.3Lift:
  • Association Analysis is simply a search through the data for combinations of items whose statistics are interesting. It helps us establish rules dictating something like “If A occurs then B is likely to occur as well.”
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