New method to improve predictions

NEW YORK: A team of researchers has created a new method to analyse big data that better predicts outcomes in healthcare, politics and other fields.

In an effort to reduce the error rate with methods like using a significance-based criterion for evaluating variables to find highly predictive variables, researchers at Princeton, Columbia and Harvard universities in the US proposed a new measure called the influence score, or I-score, to better ability to predict.

In their study, to be published in journal Proceedings of the National Academy of Sciences, researchers found that the I-score is effective in differentiating between noisy and predictive variables in big data and can significantly improve the prediction rate.

“The practical implications are what drove the project, so they are quite broad,” lead author Adeline Lo said. measure a variable’s

“That the I-score fares especially well in high dimensional data and with many complex interactions between variables is an extra boon for the researcher or policy expert interested in predicting something with large dimensional data,” Lo, who is a postdoctoral researcher in Princeton’s Department of Politics, added.

The I-score improved the prediction rate in breast cancer data from 70 per cent to 92 per cent.

— AFP People take part in the 7th Edition of the Nautic SUP Paris Crossing stand up paddle competition on the River Seine, in Paris, on Sunday.