SVR

A comparison between classical (ARIMA) forecasting methods for time series and regression based on Support Vector Machines. A huge set of economic time series is available to train and validate foreasting methods

Skills required: basic computer science skills; python might be the language of chooice

Image credits: http://www.ece.umn.edu/users/cherkass/ee4389/SVR.html

Candidate: Alberto Paruta. Start: may 2016

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Forecasting time series with Support Vector Regression