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Activity Number: 480
Type: Topic Contributed
Date/Time: Wednesday, August 12, 2015 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistical Computing
Abstract #316867
Title: Automated Forecasting with Big Data
Author(s): Sean Taylor* and Alex Peysakhovich
Companies: Facebook and Facebook
Keywords: forecasting ; big data ; machine learning ; sensors
Abstract:

We describe the challenges and opportunities of forecasting thousands or even millions of related time series. Our approach is to place the extrapolation problem in a statistical learning framework fit large models which directly minimize empirical risk across many forecast horizons. We show how combining streaming feature generation with scalable regularized regression techniques can produce good forecasts and predictive intervals for extremely large data sets. We call the resulting system "Prophet," and it is currently used at Facebook to almost completely automate forecasting across a wide variety of problems.


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