Projection error evaluation for large multidimensional data sets

摘要

This research deals with projection error evaluation for large data sets using onlya personal computer without any particular technologies for high performance computing.A shortcoming of basic projection error calculation ways is such that they require a large amountof computer memory or computation time is not acceptable when large data sets are analyzed. Thispaper proposes two ways for projection error evaluation: the first one is based on calculating theprojection error for not full data set, but only for representative data sample, the second one obtainsthe projection error by dividing a data set into the smaller data sets. The experiments have beencarried out with twelve real and artificial data sets. The computational efficiency of the projectionerror evaluation ways is confirmed by a comprehensive set of comparisons. We demonstrate thatdividing data set into the smaller data sets allows us to calculate the projection error for large datasets.