1. A method comprising: sampling a plurality of data points in a first domain; transforming the sampled data points from the first domain to a second domain, wherein the transformed data points include a plurality of identified data points of interest in the second domain; predicting future data points based on a forecast rule set and the plurality of data points of interest transformed to the second domain; comparing the plurality of data points of interest transformed to the second domain with corresponding data points of interest included in the predicted future data points; calculating an error measure based on the comparison; determining if the error measure exceeds an error threshold; and if the error measure exceeds the error threshold, invoking a re-initialization process.