1. A method for event detection permitting per event adjustment of false alarm rate, comprising the steps of: loading operational data; loading background data; comparing said operational data to said background data; determining from said step of comparing, whether said operational data contains predictive data; tagging predictive data at the time when and where it occurs; extracting and reporting statistical features from said predictive data; selecting said statistical features of choice so as to form at least one feature vector; associating into a plurality of clusters, patterns formed by said at least one feature vector according to the character of said predictive data and said time at which it occurred; optimizing false alarm thresholds and detection rates for each of said plurality of clusters; detecting events; and feeding back results.