Abstract:

The authors proposed two confidence estimating methods, namely, K-nearest and maximum distinction methods, which were practized with selected certain percentage of data in the UCI datasets, compared macrorecall, macroprecision and time loss, and proved the effectiveness of maximum distinction. The results show the improvement of confidence evaluation in semisupervised classification.

Key words: confidence evaluation, classification, semisupervised learning, K-nearest algorithm