Trinity College Dublin, Department of Computer Science
Carney, Michael; Cunningham, Pádraig; Dowling, Jim. 'Predicting Probability Distributions for Surf Height Using an Ensemble of Mixture Density Networks'. - Dublin, Trinity College Dublin, Department of Computer Science, TCD-CS-2006-06, 2006, pp14
Computer Science Technical Report TCD-CS-2006-06
There is a range of potential applications of Machine Learning where it would be more useful to predict the probability distribution
for a variable rather than simply the most likely value for that variable. In meteorology and in finance it is often important to know the
probability of a variable falling within (or outside) different ranges. In
this paper we consider the prediction of surf height with the objective of
predicting if it will fall within a given ‘surfable’ range. Prediction problems such as this are considerably more difficult if the distribution of the
phenomenon is significantly different from a normal distribution. This
is the case with the surf data we have studied. To address this we use
an ensemble of mixture density networks to predict the probability density function. Our evaluation shows that this is an effective solution. We
also describe a web-based application that presents these predictions in
a usable manner.
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