Dassweb - "TIME SERIES FORECASTING: SOME CHALLENGES AND POSSIBLE SOLUTIONS"

March 16th | 17h00

DaSSWeb, Data Science and Statistics Webinar
"TIME SERIES FORECASTING: SOME CHALLENGES AND POSSIBLE SOLUTIONS"
Luís Torgo | Canada Research Chair on Spatiotemporal Ocean Data Analytics and a Professor of Computer Science at the Dalhousie University

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Abstract

With the widespread availability of a multitude of data collection devices measuring different properties frequently in real time, time series forecasting is becoming increasingly important for many application domains. Approaches from many research disciplines (e.g. statistics, econometrics, machine learning, etc.) are available to practitioners and researchers.  All these facts raise several challenges that we will discuss during this talk. We will describe alternative methods for correctly evaluating and comparing these approaches, thus facilitating the relevant task of model selection. We will also address some of the reasons leading to models performing rather differently across diverse application domains. Finally, we discuss how approaches based on ensembles can help in overcoming some of these difficulties.

Short bio
Luis Torgo is a Canada Research Chair (Tier 1) on Spatiotemporal Ocean Data Analytics and a Professor of Computer Science at the Dalhousie University, Canada.
He is also an Associate Professor of the Department of Computer Science of the Faculty of Sciences of the University of Porto, Portugal, and an invited professor of the Stern Business School of the New York University where he has been collaborating since 2014 in the Master of Science in Business Analytics. He is a member of the Institute for Big Data Analytics at Dalhousie, and he is also a senior researcher of LIAAD / INESC Tec.
He has been doing research in the area of Data Mining and Machine Learning since 1990, and has published over 100 papers in several forums of these areas. His current broad research interests revolve around analyzing data from dynamic environments, with a particular focus on time and space-time dependent data sets, in the search for unexpected events. In terms of application domains his research is frequently linked with ecological/biological as well as financial domains.

Presentation