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Kaggle competitions: Tourism Forecasting, Chess


 
  
Tourism Forecasting Part 1 ended, Part 2 starting; Who competes; Halfway report on Chess/Elo ratings competition


Kaggle New competition: Tourism Forecasting Part Two
Tourism Forecasting Part Two has just launched. This part requires participants to forecast 366 monthly time series and 427 quarterly time series. The overall winner will collect $AUD500 and will be invited to contribute a discussion paper to the International Journal of Forecasting describing their methodology and results.

Competition results: Tourism Forecasting Part One
Tourism Forecasting Part One has just ended. The winner was Lee Baker, an embedded systems engineer from Las Cruces, New Mexico in the United States. Lee has promised to send through a write-up, which we will post on the Kaggle blog. This was a hotly contested competition, with 21 teams beating the best performing method in Athanasopoulos, Hyndman, Song and Wu (2010).

Who competes in data prediction competitions?
No Free Hunch, the Kaggle blog, has an overview of the Kaggle user base based on members' profile pages. The 'typical' user is an American (often an academic) who is trained in computer science, prefers using R and neural networks.

Elo vs the Rest of the World at the halfway mark,
Posted by Jeff Sonas on September 21, 2010

We have just passed the halfway mark of the "Elo vs the Rest of the World" contest, scheduled to end on November 14th. The contest is based upon the premise that a primary purpose of any chess rating system is to accurately assess the current strength of players, and we can measure the accuracy of a rating system by seeing how well the ratings do at predicting players' results in upcoming events. The winner of the contest will be the one whose rating system does the best job at predicting the results of a set of 7,800 games played recently among players rated 2200+.

A wide range of approaches have been tried, including almost every known chess rating system as well as other tries involving neural networks, machine learning, data mining, business intelligence tools, and artificial intelligence. In fact over 1,600 different tries have been submitted so far, and we anticipate far more submissions as the competition heats up over the final seven weeks.

The #1 spot is currently held by Portuguese physicist Filipe Maia, who confesses to little knowledge about statistics or chess ratings, but is nevertheless managing to lead the competition! He is also the author of El Turco, the first-ever Portuguese chess engine. Out of the current top ten teams on the leaderboard, seven use variants of the Chessmetrics rating system, two are modified Elo systems, and one is a "home-grown variant of ensemble recursive binary partitioning". That last approach belongs to the #3 team on the public leaderboard, a team known as "Old Dogs With New Tricks". This team is a collaborative effort between Dave Slate and Peter Frey, both prominent leaders in computer chess for many years.


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