发明名称 |
PARTIALLY SUPERVISED MACHINE LEARNING OF DATA CLASSIFICATION BASED ON LOCAL-NEIGHBORHOOD LAPLACIAN EIGENMAPS |
摘要 |
A local-neighborhood Laplacian Eigenmap (LNLE) is provided for methods and systems for semi-supervised learning on manifolds of data points in a high-dimensional space. A labeled set and unlabeled data points are received as seen in Figure 4 (402). An adjacency Matrix/Graph is built (404). An unlabeled point is selected (406), then a local neighborhood/subgraph is found (408). Next, a Local Eigen Decomposition is computed (41) and evaluated (412) and the point is classified (414). A check is made to see if more points are available (416). If more points are available, select an unlabeled point (4Q6), otherwise output the classification (418).
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申请公布号 |
WO2006113248(A3) |
申请公布日期 |
2009.05.22 |
申请号 |
WO2006US13566 |
申请日期 |
2006.04.11 |
申请人 |
HONDA MOTOR CO., LTD.;RIFKIN, RYAN;ANDREWS, STUART |
发明人 |
RIFKIN, RYAN;ANDREWS, STUART |
分类号 |
G06F15/18 |
主分类号 |
G06F15/18 |
代理机构 |
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