Using supervised classifiers with unsupervised data

Data processing: artificial intelligence – Machine learning

Reexamination Certificate

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Reexamination Certificate

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11005136

ABSTRACT:
In one embodiment, a method includes converting unsupervised data into supervised data using multiple processes and training multiple supervised classifiers with the supervised data of the processes. In such manner, supervised classifiers may be used to classify unsupervised data. Affinity measures may be determined and data clustered using the resulting trained classifiers. Other embodiments are described and claimed.

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Andrew W. Moore “K-means and Hierarchical Clustering” www.cs.cmu.edu. Nov. 16, 2001.
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Wald, Lecture II, “Looking inside the Black Box”, Leo Breiman, http://stat-www.berkeley.edu/users/breiman/wasI2002-2.pdf. pp. 19-35. Feb. 2002.
Andrew Y. Ng, Michael I. Jordan, Yair Weiss. “On Special Clustering: Analysis and an algorithm”. 2001.
E.M. Kleinberg, “On the algorithmic implementation of stochastic discrimination”, IEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-22, May 5, 2000, Abstract.
Dechang Chen, Peng Huang and Xiuzhen Cheng. “A concrete statistical realization of Kleinberg's stochastic discrimination for pattern recognition. Part I. Two-class classification” Source: Ann. Statistic. 31 (2003), No. 5. Abstract.

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