1. A method, comprising determining a value for each feature in a group of features provided by a training data; eliminating at least one feature with one of a minimum value and a maximum value from the group; retrieving a kernel data from a buffer; subtracting a matrix from the kernel data to provide an updated kernel data, each component of the matrix comprising a dot product of two of training samples provided by at least a part of the training data that corresponds to the eliminated feature; updating the value for each feature of the group based on the updated kernel data; repeating of eliminating the at least one feature from the group and updating the value for each feature of the group until a number of features in the group reaches a predetermined value to generate a feature ranking list; recognizing a new data corresponding to the group of features with the feature ranking list.