13. A system, comprising: a data store storing training images for training an image classification model for an n-gram, the training images including positive images having relevance measures, for the n-gram, that meet a relevance threshold and negative images having relevance measures, for the n-gram, that do not meet the relevance threshold; and an image classification system coupled to the data store, the image classification system including one or more processors configured to train the image classification model for the n-gram based on feature vectors of the training images, the image classification model comprising scalars corresponding to the feature vectors and a minimum kernel of feature vectors of training images.
14. The system of claim 13 , wherein the image classification system is further configured to classify a training image based on the image classification model and adjust the image classification model based on a feature vector of an inaccurately classified training image based on the image classification model.