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tex/2_lit/3_ml/1_intro.tex

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+\subsection{Demand Forecasting with Machine Learning Methods}
+\label{ml_methods}
+
+ML methods have been employed in all kinds of prediction tasks in recent
+    years.
+In this section, we restrict ourselves to the models that performed well in
+    our study: Random Forest (\gls{rf}) and Support Vector Regression
+    (\gls{svr}).
+RFs are in general well-suited for datasets without a priori knowledge about
+    the patterns, while SVR is known to perform well on time series data, as
+    shown by \cite{hansen2006} in general and \cite{bao2004} specifically for
+    intermittent demand.
+Gradient Boosting, another popular ML method, was consistently outperformed by
+    RFs, and artificial neural networks require an amount of data
+    exceeding what our industry partner has by far.