| 摘要 |
A method, system and computer program product for scaling, or dimensionally reducing, multi-dimensional data sets, that scales well for large data sets. The invention scales multi-dimensional data sets by determining one or more non-linear functions between a sample of points from the multi-dimensional data set and a corresponding set of dimensionally reduced points, and thereafter using the non-linear function to non-linearly map additional points. The additional points may be members of the original multi-dimensional data set or may be new, previously unseen points. In an embodiment, the invention begins with a sample of points from an n-dimensional data set and a corresponding set of m-dimensional points. Alternatively, the invention selects a sample of points from an n-dimensional data set and non-linearly maps the sample of points to obtain the corresponding set of m-dimensional points. |
