Wednesday, October 28, 2009

Predictive Analytics World, part 1

After attending Predictive Analytics World (PAW) last week, I must say that I'm still impressed with the conference, especially for practitioners.

Eric Siegel's description of uplift modeling in the opening session was another example of a practical (and in this case, relatively new) approach to predictive modeling. I only heard about uplift modeling for the first time (to my discredit) at the February PAW, and almost had a company implement it this past summer were it not for a re-org that killed the modeling efforts.

The R community had another strong showing, with REvolution being there, and another R useR meeting. I'm amazed at the influence of R in the data mining world. It makes me want to become fluent in R! Just on the list.

The keynotes by Usama Fayyad and Stephen Baker were every bit as good as one would expect, but it was the interactions with attendees that impressed me most. The talk I gave received great questions about the practice of using ensembles by several folks who were planning on using this technique with their own data. It's this practical side to the conference that I liked.


Tim Manns said...

Hi Dean,

Your presentation made me an emsemble convert! I previously hadn’t given ensembles much thought, but I was surprised that ensembles could provide robustness, or that a simple mathematical average would be used! (I thought some form of weighting would be the norm)

I'm planning on testing a few ensembles next week. I’ll let you know who they go on large datasets in a telecom space.

btw – I really enjoyed meeting up and having a few beers. Sorry my attendance was so brief.

- Tim

Jeff said...

For those interested, one of the first papers (I saw) on the subject of incremental lift modeling is here:

Portrait Software has tools dedicated to this as well:

Sandro Saitta said...

Thanks for the feedback Dean. I hadn't the chance to attend this event, but I'm happy to read some info about it.