FICO, a leading provider of analytics and decision management technology, and the University of California, San Diego (UCSD) have announced the winners of the seventh annual UCSD-FICO Data Mining Contest.
Participants from six countries on four continents were among the winners who developed predictive analytics to determine which consumers were most likely to shop online.
This year, contestants were given anonymous data for more than 130,000 consumers. The data included no personally identifiable information. Based on that data, competitors built models to predict which consumers were most likely to buy products online. Participants were judged on how accurately they were able to predict future purchases.
The competition was divided into two categories — one category utilized raw data, and one category utilized transformed data — and each category had a Graduate and Undergraduate division. The top three finishers in each category and each division shared $10,000 in cash prizes.
“Students around the world look forward to the UCSD-FICO Data Mining Contest each year as an opportunity to put the skills they've learned in the classroom to use in a rigorous real-world competition,” said professor Charles Elkan of UCSD's Department of Computer Science and Engineering.
“It's been exciting to see the growth of this competition since its inception, with over 140 participants from six continents competing this year. We are proud of all the students who participated, and we appreciate FICO's ongoing commitment to developing and encouraging the next generation of innovators in predictive analytics.”