11. An image classification system, comprising: a processor; a memory; where the processor is configured by software stored in memory to: receive an image hierarchy; receive a first image of interest wherein the image includes at least one feature; classify the at least one feature of the image according to the image hierarchy; generate a dual variable for a Lagrange function associated with the classification of the at least one feature, where the dual variable controls a trade-off between an information gain and an accuracy; optimize the classification of the at least one feature of the image using the dual variable controlling the trade-off between the information gain and the accuracy by generating a classifier that maximizes a relationship between the information gain and the accuracy with respect to the dual variable; and generate at least one optimized classification of the at least one feature of the image for the first image of interest.
11. An image classification system, comprising: a processor; a memory; where the processor is configured by software stored in memory to: receive an image hierarchy; receive a first image of interest wherein the image includes at least one feature; classify the at least one feature of the image according to the image hierarchy; generate a dual variable for a Lagrange function associated with the classification of the at least one feature, where the dual variable controls a trade-off between an information gain and an accuracy; optimize the classification of the at least one feature of the image using the dual variable controlling the trade-off between the information gain and the accuracy by generating a classifier that maximizes a relationship between the information gain and the accuracy with respect to the dual variable; and generate at least one optimized classification of the at least one feature of the image for the first image of interest. 12. The image classification system of claim 11 , wherein the image hierarchy is a semantic hierarchy.