基于Boosting的高光谱遥感切空间协同表示集成学习方法
虞瑶,苏红军,姚文静

Boosting Ensemble Learning for Hyperspectral Image Classification Using Tangent Collaborative Representation
Yao Yu,Hongjun Su,Wenjing Yao
表2 实验一分类精度统计
Table2 Classification Accuracy Statistics of Experiment 1
类别训练样本测试样本BoostingRFELMTCRCAdaBoost ELMBoost TCRC
道路151 27282.6082.2089.6788.9191.1392.44
草地151 09989.7890.9389.1285.5495.2989.49
阴影1520471.0394.0266.3190.4681.8788.43
土壤1536473.2494.4580.6686.8286.8591.19
树木151 33698.6893.4999.1598.1899.3398.89
建筑物151 27083.7279.6789.6094.6387.3296.17
总体分类精度/%86.0987.3189.3690.9191.9293.73
平均分类精度/%83.1889.1385.7590.7690.3092.77
Kappa系数0.825 70.841 30.866 50.888 50.898 30.920 8
时间/s1.250.100.1418.401.30126.95