基于合群度-隶属度噪声检测及动态特征选择的改进AdaBoost算法

王友卫,凤丽洲

Improved AdaBoost algorithm using group degree and membership degree based noise detection and dynamic feature selection

You-wei WANG,Li-zhou FENG

表 4 不同特征选择方法对应的时间复杂度比较

Tab.4 Comparison of time complexities of different feature selection methods

特征选择方法 时间复杂度 IG ${ {O} }\left( {N\left( {M + L + ML + {\rm{log_2\;} }N} \right)} \right)$ CHI ${ {O} }\left( {N\left( {M + {\rm{3} }L + {\rm{2} }ML + {\rm{log_2\;} }N} \right)} \right)$ MRMR ${{O} } \left( {\displaystyle\sum\limits_{S = 0}^{ {N_1} - 1} {S\left( {N - S} \right)\left( {2M + 2L} \right)} } \right)$ CMFS ${ {O} }\left( {N\left( {M + L + ML + {\rm{log_2\;} }N} \right)} \right)$ IGW ${ {O} }\left( {N\left( { {\rm{2} }M + L + ML + {\rm{log_2\;} }N} \right)} \right)$ CHIW ${ {O} }\left( {N\left( { {\rm{2} }M + {\rm{3} }L + ML + {\rm{log_2\;} }N} \right)} \right)$ MRMRW ${{O} } \left( {\displaystyle\sum\limits_{S = 0}^{ {N_1} - 1} {\left( {N - S} \right)\left( {S\left( {2M + 2L} \right) + M} \right)} } \right)$ CMFSW ${ {O} }\left( {N\left( { {\rm{2} }M + L + ML + {\rm{log_2\;} }N} \right)} \right)$