Patent ID: 8918347

Claim:
A method for computer-based selection of identifying input for differentiating classes, the method comprising: specifying, by a training region specifying module, a plurality of training regions in a training space, wherein the training regions are representative of a plurality of defined classes, wherein training data associated with the training space are organized into data bands according to selected definitions, wherein each of the training regions has at least one training location with a training element associated with each of the data bands, wherein a first training element has a training element size that comprises a count of the number of bits in the first training element and a first training window at a window position, wherein the first training window has a value comprising a data symbol and a window size comprising a count of the number of bits in the first training window, and wherein the window size is less than or equal to the training element size; determining a relevance measure for the first training window, wherein the relevance measure represents an extent of likelihood of correctly identifying class for a test location based on: a window within a test element associated with the test location and at the window position of the first training window, a data band with which the test element is associated, and the frequency of occurrence of data symbols in training windows at the window position of the first training window; and selecting, by a most relevant window module, the first training window as a most relevant window when the relevance measure of the first training window is greatest relative to relevance measures for other training windows, selecting, by an identifying input selection module, the most relevant window, together with its associated data band, window position, and window size, as the identifying input for conducting the class differentiation.