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Regular version of the site

Book chapter

Learning hypotheses from triadic labeled data

P. 474-480.
Ignatov D. I., Zhuk R., Konstantinova N.

We propose extensions of the classical JSM-method andtheNa ̈ıveBayesianclassifierforthecaseoftriadicrelational data. We performed a series of experiments on various types of data (both real and synthetic) to estimate quality of classification techniques and compare them with other classification algorithms that generate hypotheses, e.g. ID3 and Random Forest. In addition to classification precision and recall we also evaluated the time performance of the proposed methods. 

 

In book

Edited by: D. Slezak, H. S. Nguyen, M. Reformat et al. Los Alamitos; Washington; Tokyo: IEEE Computer Society, 2014.