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Abstract
The tolerant rough set classifier (TRSC) was introduced for land cover classification. TRSC uses a tolerance relation to define the tolerant rough set of each object to be classified, and then classifies the object using the relative frequency of each class in the lower approximation or boundary of its tolerant rough set. According to the overall accuracy, the κ coefficient, the total normalized probability of misclassification (TNPM) and McNemar's test, the result of TRSC was better than that of the minimum distance classifier (MDC), and similar to those of the maximum likelihood classifier (MLC) and the multiplayer perceptron (MLP).
Acknowledgements
This study was supported financially by the National Nature Science Foundation of China (No. 40571100). We thank the anonymous reviewers for their valuable comments on the manuscript.
