My last post discussed a method to decode a substitution cipher using a Metropolis-Hastings algorithm. It was brought to my attention that this code could be improved by using Simulated Annealing methods to jump around the sample space and avoid some of the local maxima. Here is a basic description of the difference: In...
There is a data mining competition with a prize of $3,000,000. The target is to improve healthcare in US by identifying patients who will be admitted to a hospital within the next year, using historical claims data. The algorithm to … Continue reading →
This past Saturday, I hung out at the Seattle branch of the International Open Data Hackathon. The event was hosted at the Pioneer Square office of Socrata, a small company that helps governments provide public open data. A pair of data analysts f...
Here are the presentation slides I used for my talk on “Using R for Data Mining Competitions” at Ryerson University as part of the Greater Toronto Area (GTA) R User’s Meetup Group. Presentation (Prezi) Meetup Event page Special thanks to Anthony Goldbloom from Kaggle and various competition winners for sharing their code and winning...
<< My review of Day 1.
I am summarizing all of the days together since each talk was short, and I was too exhausted to write a post after each day. Due to the broken-up schedule of the KDD sessions, I group everything together instead of switching back and forth among a dozen different topics....
I have been waiting for the KDD conference to come to California, and I was ecstatic to see it held in San Diego this year. AdMeld did an awesome job displaying KDD ads on the sites that I visit, sometimes multiple times per page. That’s good targeting!
Mining and Learning on Graphs Workshop 2011
I had...
I like politics; I don’t like all of the lying involved. If you ask me, I think that there should be “Ethics Committee” investigations into all of the lying. Sure, tweeting a picture of your junk is probably not the … Continue reading →
Last Saturday I had the good fortune to present a talk on finding, gathering, and analyzing some sports-related data on the web at the local SABR group meeting. In case you’re not familiar with the “SABR” acronym, it stands for … Continue reading →
One of the recurring frustrations in data analytics is that your data is never in the right shape. Worst case: you are not aware of this and every step you attempt is more expensive, less reliable and less informative than you would want. Best case: you notice this and have the tools to reshape...
Kaggle has released a new data-mining challenge: use data from 10 years of Wikipedia edits in order to predict future edit rates. The dataset has been anonymized in order to obscure editor identity and article identity, simultaneously adding focus to the challenge and robbing the dataset of considerable richness. I have some experience with...
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).