1. A method of classifying the material type of an unknown material into a probability distribution of multiple predetermined material types by using a collection of plural predetermined material classifiers, wherein each material type of the multiple predetermined material types is associated with a corresponding best performing classifier from the collection of plural predetermined material classifiers by a predesignated stored association, the method comprising the steps of: applying, using a processor, the plural material classifiers to the unknown material to obtain a list of candidate material types; looking up, using the processor, a list of potential best performing classifiers using the list of candidate material types as a reference into the predesignated stored association; and assigning, using the processor, a respective probability that the unknown material belongs to a material type based on the list of potential best performing classifiers, wherein applying comprises obtaining one or more feature vectors for the unknown material and inputting a corresponding one of the feature vectors into each of the plural material classifiers so as to obtain an output representative of material type from each of the plural material classifiers.