Random Sampling Subspace Locality Preserving Projection (RSSLPP) method is proposed to improve the recognition performance of a single Locality Preserving Projection (LPP).
针对单一保局投影(LPP)算法分类识别能力弱的问题，提出了一种随机采样子空间保局投影算法(RSSLPP)。
Different priority rules are adopted in the random sampling procedure, and a statistical test shows that they affect the performance of the proposed random sampling method.
通过对比分析，说明不同的任务优先规则对随机抽样算法具有不同的影响，其中采用MINSLK等优先规则的随机抽样算法能够有效地缩短项目平均工期。
Different priority rules are adopted in the random sampling procedure, and a statistical test shows that they affect the performance of the proposed random sampling method.
通过对比分析，说明不同的任务优先规则对随机抽样算法具有不同的影响，其中采用MINSLK等优先规则的随机抽样算法能够有效地缩短项目平均工期。
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