Transductive Learning: Learning Iris Data with Two Labeled Data

Authors:
Chun Hung Li;Pong Chi Yuen
Affiliations:
-;-
Venue:
ICANN '01 Proceedings of the International Conference on Artificial Neural Networks
Year:
2001

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Abstract

This paper presents two graph-based algorithms for solving the transductive learning problem.Sto chastic contraction algorithms with similarity based sampling and normalized similarity based sampling are introduced.The transductive learning on a classical problem of plant iris classification achieves an accuracy of 96% with only 2 labeled data while previous research has often used 100 training samples.The quality of the algorithm is also empirically evaluated on a synthetic clustering problem and on the iris plant data.