1. A method for selecting a set of training data from a set S of samples from a machine condition monitoring system, the selected set of training data being for use in training a statistical model for evaluating measurements in the machine condition monitoring system, the method comprising the steps of: performing the following steps for each sample p from the set S: calculating a distance from the sample p to a node of a kd-tree, wherein each node of the kd-tree is empty or represents another sample removed from the set S; if the calculated distance is greater than a distance threshold r max , and the node of the kd-tree has children, calculating a distance from the sample p to a child of the node selected according to a classification of p in the kd-tree; repeating the previous step until either the calculated distance is below the distance threshold r max , or the node of the kd-tree has no children; and if no calculated distance is below the distance threshold r max , then populating a next leaf in the kd-tree with p; and using the nodes of the kd-tree as the set of training data.