THE EFFECTIVENESS OF NON-PARAMETRIC CLASSIFIERS IN A LIMITED TRAINING SET
Aleksey A Romanov, Kirill A Rubanov
Abstract
This paper presents a comparative analysis of the effectiveness of the method of support vector machine and artificial neural networks for classification of satellite images medium spatial resolution as an example of a high degree of heterogeneity and limited training data. The results of field-based researches have been used for test cases generation. Neural network approach showed the best result for classification accuracy (89.9% vs. 86.2% support vector), but was significantly less speed.