Method for clustering decision trees in data classifiers

Details Method for clustering decision trees in data classifiers Method for clustering decision trees in data classifiers

G - Physics

06

F

G06F 17/30 (2006.01)

Patent

CA 2494799

A method for clustering decision trees that in one embodiment can be implemented in a genetics-based data classifier for the purpose of speeding up the classification process and increasing the classification accuracy. The present invention relates to a decision tree clustering method whereby, in order the increase the classification speed and accuracy of a data classifier using groups of decision trees, similar decision trees are identified and clustered. When the method is presented with a group of decision trees encoding in each of their leaf nodes a class from the same group of classes, the method identifies similar decision trees where two decision trees are said to be similar if all the data instances correctly classified by a first decision tree are included in the set of data instances correctly classified by a second decision tree, in which case the second decision tree is said to be greater or equal than the first decision tree. The clustering is performed by placing a decision tree in the same cluster with another decision tree that is greater or equal to it, and the process is repeated until no more clustering is possible.

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