We’ve been doing this podcast for over three years and I’m surprised that we had never come across and discussed the topic of association rules. Association rules is a mining technique that allows you to find rules in your data. It’s pretty intuitive when you see it but we were so surprised how hard it was to talk about during the show.
Some resources that we encountered to get our head around the topic:
- We take a look at this example: http://www.saedsayad.com/association_rules.htm during our conversation
- Association Rules: https://towardsdatascience.com/association-rules-2-aa9a77241654
- mlxtend Association rules documentation and example: http://rasbt.github.io/mlxtend/user_guide/frequent_patterns/association_rules/
- Extracting Rules from Medical Health Records: https://www.sciencedirect.com/science/article/pii/S1877050917319658
- Association Rule Learning Wikipedia Article: https://en.wikipedia.org/wiki/Association_rule_learning
We know that talking about some of these topics is difficult and sometimes it’s hard to follow and sometimes we don’t actually convey the message easily. We hope that our conversations spark some ideas, ignite you to try some of the code yourself, or do your own research.
Please email us if our shows have spoken to you in way way or another. Also, the first person to email us will get a Data Science Imposters Podcast face mask.