Filtering Rules by Minimum Support and Confidence, Ranking by Lift
This lesson is part of the course
In this lesson
You apply minimum support and confidence to 14 candidate rules, count the survivors, rank them by lift and pull out the strongest rule, and see why the rule with the biggest lift drops out.
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Lessons in this course
- Baskets as 0/1 Rows: Item Frequency and Support Locked
- Pair Support with SUMPRODUCT: the Co-Occurrence Matrix Locked
- Confidence A → B: How Often B Follows A Locked
- Lift: Is the Rule Better than Chance? Locked
- Leverage and Conviction: Size and Direction of a Rule Locked
- Filtering Rules by Minimum Support and Confidence, Ranking by Lift Locked
- The Apriori Idea: Pruning 3-Item Sets Before You Count Them Locked
- From Rules to Cross-Selling: Expected Uplift per Recommendation Locked