Patent ID: 7974476

Claim:
A method for performing Modified Quadratic Discriminant Function (MQDF) training with flexible compression in a pattern recognition system, the method comprising: receiving, by a computing device, a plurality of training data sets for each of a plurality of classes; featurizing, by the computing device, each training data set; generating, by the computing device, a mean and a covariance matrix for each of the plurality of classes; clustering the covariance matrices, utilizing a predefined compression factor, to generate shared covariance matrices, the predefined compression factor comprising a compression factor, within a predetermined range of compression factors, wherein within the predetermined range of compression factors, there is a slight variation in isolated character classification rates between each of the compression factors in the range, the slight variation being indicative of a significant memory space reduction without at least one of a corresponding error increase and a classification accuracy degradation in the pattern recognition system; performing, by the computing device, MQDF classifier training for each of the plurality of classes using the mean for each of the plurality of classes and the clustered covariance matrices; and assigning, by the computing device, a different number of principal components to at least a portion of each of the plurality of classes; and storing, by the computing device, in a reduced memory space, the principal components of the class covariance matrices, as a result of the clustering of the covariance matrices and the assigning of the different number of the principal components to at least a portion of each of the plurality of classes.