ABSTRACT
To test whether a prediction algorithm has any true predictive power, it is necessary to compare its performance with that expected under various well-de–ned null hypotheses. These null hypotheses must include the assumption that the prediction algorithm lacks any true predictive power. In the context of studies investigating the predictability of epileptic seizures, two approaches have been introduced for this purpose: analytical performance estimates (Schelter et al. 2006a; Snyder et al. 2008; Winterhalder et al. 2003; Wong et al. 2007) and seizure predictor surrogates based on constrained randomizations of the original seizure predictor (Andrzejak et al. 2003; Kreuz et al. 2004).
