US 2002/0161763 A1 · Method for classifying data using clustering and classification algorithm supervised

Abstract

A method for classifying data involves receiving a set of training data from a physical process such as a computer network (20). The training data has attribute data and target data. The target data has a class label associated with the attribute data. Dummy clusters are derived from centroid coordinates of the training data associated with the class label (22). Distance measures are determined between the training data and a plurality of clusters which include the dummy clusters (24). Real clusters are created in the plurality of clusters if the training data is closest to a dummy cluster or a cluster having a class label different than the class label associated with the training data (26). A closest match between data to be classified and the plurality of clusters is identified (28) and the data is classified as the class label of the closest match from the plurality of clusters (30).

Claims24

Dependent claims

A method for classification of data, comprising:

providing first data from a physical process, the first data including a class label associated with attributes of the first data;
deriving a dummy cluster from centroid coordinates of the first data associated with the class label;
determining distance measures between the first data and a plurality of clusters which include the dummy cluster;
creating a real cluster in the plurality of clusters if the first data is closest to the dummy cluster;
identifying a closest match between second data and the plurality of clusters;
and
classifying the second data based on a class label of the closest match from the plurality of clusters.

4 more elements

A digital storage medium encoded with a computer program which classifies data, the computer program comprising:

first instructions for providing first data from a physical process, the first data including a class label associated with attributes of the first data;
second instructions for deriving a dummy cluster from centroid coordinates of the first data associated with the class label;
third instructions for determining distance measures between the first data and a plurality of clusters which include the dummy cluster;
and
fourth instructions for creating a real cluster in the plurality of clusters if the first data is closest to the dummy cluster.

2 more elements

Dependencies are inferred from the claim text.

Method for classifying data using clustering and classification algorithm supervised

Life of this patent

Method for classifying data using clustering and classification algorithm supervised

Life of this patent

Abstract

Claims24