Figure 2

Training algorithm. Training algorithm of the method. Here YES (NO) denotes the set of positive (negative) training sequences, including nYES (nNO) number of instances, which are tested with a window of a length n; MatrixYES (MatrixNO) are corresponding co-occurrence matrices with coordinates i and j; k denotes the subsequent number of a positive training sequence, M _k is a temporary positive correlation matrix obtained up to the k-th sequence, a denotes the beginning position of a tested window; X is the normalized sum of all previously calculated matrices M; l is an iteration counter; w denotes distance between current positive and negative co-occurrence matrices, w _d is the maximal distance later used in the classification.