This Algorithm Is Better At Predicting Human Behavior Than Humans Are

Analyzing big data sets in order to forecast trends or predict customer behavior usually relies on both computers and humans. Computer algorithms are advanced enough to rapidly comb through numbers and find useful patterns, and humans are still necessary for setting the parameters and analyzing the results. But an algorithm created by two MIT researchers suggest we could take out the human factor all together. Conceived by Max Kanter, a MIT graduate student in computer science, and his advisor, Kalyan Veeramachaneni, the Data Science Machine can approximate human “intuition” when it comes to data analysis. Using raw datasets to make models that predict things like when a student is most at risk of dropping a course, or whether a retail customer will turn into a repeat buyer, its creators claim…


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