A method of abnormal geological zone identification
The article proposes a new approach to the identification of zones with rare anomalous event of geological processes. The approach is based on two one-class classification methods of machine learning: the method of minimum area of alarm and the method of preference. the method of minimum area of alarm is nonparametric. It is trained on a sample of anomalous events and computes the field of anomalous zones. The knowledge obtained by this method is non-verbalized. The method of preference allows you to approximate the resulting solution using a simple logical rule that defines the anomalous region in terms of the analyzed properties of the geological environment. There are examples of the application of this approach: to find areas of possible foci of strong earthquakes, and for the regional forecast of deposits are considered.