1. A computer-implemented method comprising: using a computer comprising a processor to perform: initializing a model, the model including a plurality of classes; selecting subsets of patterns from a set of available patterns in a training instance selected from a training set of training instances, the selecting subsets including selecting a subset of size-1 patterns and selecting a subset of size-2 patterns; initializing a weight of each size-1 pattern in the subset of size-1 patterns; including each size-1 pattern in the subset of size-1 patterns in each class in the plurality of classes in the model; calculating an overall significance value of each size-2 pattern in the training instance; sorting the size-2 patterns using the overall significance; selecting the highest k sorted size-2 patterns; initializing a weight of each selected highest k size-2 pattern; adjusting the weights on the size-1 and size-2 patterns; and presenting the model organized with the plurality of classes, each class including the size-1 patterns, the highest k size-2 patterns, and the weights of the size-1 and size-2 patterns.