I'm learning about association rules and came across the common interestingness measures support, confidence, lift and conviction.
I'm interested in the intuition behind your decision-making process while dealing with those measures. What I'm looking for is practical advice which I can apply during my data analysis projects.
For example, the second answer from Gericke Potgieter gives a good rule of thumb (high lift, low conviction) for determining the reliability of a discovered rule.
Some intuition which I commonly use:
higher support --> rule applies to more records higher confidence --> chance that the rule is true for some record is higher higher lift --> chance that the rule is just a coincidence is lower higher conviction --> ?
What is your opinion about my intuition?
What are some of the heuristics/rules of thumb you use for making decisions regarding the above-mentioned measures?