Massachusetts Institute of Technology (MIT) researchers have developed an approach to automating most of the process of big data analysis.
The researchers say their new system could perform tasks that normally take months, in just a matter of days.
"The goal of all this is to present the interesting stuff to the data scientists so that they can more quickly address all these new data sets that are coming in," says MIT researcher Max Kanter.
The researchers have written two papers on the topic, both focusing on time-varying data, which reflects observations made over time.
The first paper describes a general framework for analyzing time-varying data, which splits the analytic process into three stages.
The second paper describes a new language for describing data-analysis problems and a set of algorithms that automatically recombine data in different ways, to determine the types of prediction problems the data might be useful for solving.
"Probably the biggest thing here is that it's a big step toward enabling us to represent prediction problems in a standard way so that you could share that with other analysts in an abstraction from the problem specifics," says Kiri Wagstaff, a senior researcher in artificial intelligence and machine learning at the U.S. National Aeronautics and Space Administration.
From MIT News
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