19031236
submission
databuff writes:
The April 4 launch of the $3 million Heritage Health Prize was just announced by the Heritage Provider Network, a network of doctors. The competition challenges data hackers to build algorithms that predict who will go to hospital in the next year, so that preventative action can be taken. An algorithm might find that somebody with diabetes, hypertension and high cholesterol is a 90 per cent risk for hospitalization. Knowing this, it might be cheaper for an HMO to enrol them in an exercise program now rather than pay the likely hospital bill. The competition takes the same approach as $1 million Netflix Prize, but solves a far more significant problem.
17803098
submission
databuff writes:
Last week, Sydney's Minister of Roads, David Borger, launched a $10,000 competition to develop an algorithm that predicts commute times on a major Sydney freeway. The winning algorithm will be used to power predictions on the Sydney live traffic website. The hope is that the predictions will help commuters make informed decisions about when to travel and on what routes, lowering the intensity of peak hour traffic. In its first week, the competition attracted entries from more than 50 teams and 19 countries.
16445234
submission
databuff writes:
About six weeks ago, Slashdot reported a competition to find a chess rating algorithm that performed better than the official Elo rating system. The competition has just reached the halfway mark and the best entries have outperformed Elo by over 8 per cent. The leader is a Portrugese physicist, followed by an Israeli mathematician and then a pair of American computer scientists. The fact that Elo has been so comprehensively beaten is a sure sign that half a century after it was developed, it's due for an upgrade.
14805978
submission
databuff writes:
Less than 24 hours ago, Jeff Sonas, the creator of the Chessmetrics rating system, launched a competition to find a chess rating algorithm that performs better than the official Elo rating system. The competition requires entrants to build their rating systems based on the results of more than 65,000 historical chess games. Entrants then test their algorithms by predicting the results of another 7,809 games. Already three teams have managed create systems that make more accurate predictions than the official Elo approach. It's not a surprise that Elo has been outdone — after all, the system was invented half a century ago before we could easily crunch large amounts of historical data. However, it is a big surprise that Elo has been bettered done so quickly!
13017506
submission
databuff writes:
As a break from projecting the strength of subprime mortgages, credit default swaps and other obscure financial instruments, quantitative analysts at Goldman Sachs, JP Morgan, UBS and Danske Bank have modeled the 2010 FIFA World Cup. Now Kaggle has set up a forecasting competition, allowing statisticians to go head-to-head with these corporate giants. The challenge is to predict how far each country will progress in the tournament. If the banks know as much about soccer as they do about subprime mortgages, the statisticians are in with a good chance.
12588788
submission
databuff writes:
Google has released a data prediction a prediction API. The service helps users leverage historical data to make predictions that can guide real-time decisions. According to Google, the API can be used for prediction tasks ranging from product recommendations to churn analysis (predicting which customers are likely to switch to another provider). The API involves three simple steps, upload the data, train the model and then generate predictions. The API is currently available on an invitation only basis.
11413184
submission
databuff writes:
Predictions are critical to modern life. Police predict where and when crimes are most likely to take place, banks predict which loan applicants are most likely to default and hotels forecast seasonal demand to set room rates. A new project called Kaggle facilitates better predictions by providing a platform for forecasting competitions. The platform allows organizations to post their data and have it scrutinized by the world's best statisticians. It will offer a robust rating system, so it's easy to identify those with a proven track record. Organizations can choose either to follow the experts, or to follow the consensus of the crowd — which, according to New Yorker columnist James Surowiecki, is likely to be more accurate than the vast majority of individual predictions. The power of a pool of predictions was demonstrated by the Netflix Prize, a $1m data-prediction competition, which was won by a team of teams that combined 700 models. Kaggle's first competition is underway, and it is accessing the 'wisdom of crowds' to predict the winner of this May's Eurovision Song Contest.
