Patent ID: 6351561
Filing Date: 2002-02-26
Classification: G06K,Y10S

Abstract:
A method for generating a decision-tree classifier from a training set of records, the method comprising:providing each record with at least one attribute with numerical values and a class label; initializing a set of vectors V to include one vector for each numeric attribute wherein an initial set is denoted V0, and initializing phase to 1; creating a decision tree classifier from the training set of records using hyperplanes orthogonal to the set of vectors; reinitializing V to V0; considering pairs of regions wherein each region of a pair corresponds to a leaf node in the decision tree created; discarding from consideration pairs of regions based on a size and/or an adjacency and/or a dominant class label criterion; computing for each non-discarded pair of regions a new vector using a function of the shape and extent of the regions; adding this vector to the set V; and repeating the steps of creating, reinitializing, considering, discarding, computing, and adding until phase equals a user specified maximum phase, thereby generating the decision-tree classifier.