Patent ID: 8121969
Filing Date: 2012-02-21
Classification: G01V,G06K

Abstract:
1. A method for interpreting a plurality of m-dimensional attribute vectors (m≧2) assigned to a plurality of locations in an n-dimensional interpretation space (n≧1), which method comprises the steps of arranging at least a subset of the attribute vectors as points in an m-dimensional attribute space; defining k classes (k≧2) of attribute vectors by identifying for each class at least one classification point in attribute space; postulating a classification rule for points in attribute space; determining a class-membership attribute of a point in attribute space using the classification points and the classification rule to obtain a classified point, wherein the class-membership attribute of the classified point comprises k probabilistic membership values, each representing a probability that the classified point belongs to a selected one of the k classes; and assigning a display parameter to the classified point that is related to the class-membership attribute; wherein the display parameter is a mixed display parameter derived from the probabilistic membership values.