|English: Phases of the CRISP-DM process Français : Phases du processus CRISP_DM (Photo credit: Wikipedia)|
Great keynote by Eric Siegel on understanding whether a discovery you have made is BS or not.
(Bad Science for those of you not there.)
Vast search introduces new considerations in working with predictive models in large data sets, because, in a large enough data set almost any conditions can be found.
After all, "If you torture your data long enough, it will confess to anything."
Really knowing whether any finding is valid is very important when dealing with big data.
I followed the track related to Uplift Modeling.
I will need to go through Eric's book on Uplift modeling to best understand it but the examples provided in the sessions on Day 1 were enough to not only whet the appetite, but also dive in and do some experiments.
I also met with the fine people at Elder research, it turns out we both worked on a very similar government project some years ago.
They have done some research, and applications on the integration of CRISP-DM with the Agile framework. This is most intriguing I have to follow up with them to learn more about how they married such different methodologies.
At the end of day 1 I signed up for dinner with strangers, there were three groups of about 8 folks each who were sent to various restaurants throughout New York City. We had some good conversations about our individual struggles to bring Predictive Analytics to the masses.
I made some new networking connections, and look forward to staying in touch with some really positive professionals.