1. A method of controlling a wind turbine, comprising: acquiring and storing training data relating to one or more sensed variables, wherein the training data includes a feature vector obtained from at least one statistical measure indicative of risk; assigning each of the training data to a risk category based on a measured parameter and defining feature zones for each category from at least a measure of distance of feature vectors in that category, the feature zones including a high risk zone indicative of a high risk of a gust; and during operation of the wind turbine, determining an estimate of gust risk by calculating a feature vector periodically from data obtained from at least one sensor and determining to which of the feature zones to assign the feature vector, thereby determining an estimate of the risk of an extreme gust represented by the measured feature vector, wherein the feature vector is assigned to a feature zone by measuring the mahalonobis distance from the feature vector to the centre of each feature zone and assigning the feature vector to the zone having the smallest mahalonobis distance from the feature vector; and adjusting the wind turbine to de-rate the wind turbine when the estimate of gust risk is above a threshold to prevent damage to the wind turbine.