Self-Organizing Maps
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
A Triangulation Method for the Sequential Mapping of Points from N-Space to Two-Space
IEEE Transactions on Computers
A Nonlinear Mapping for Data Structure Analysis
IEEE Transactions on Computers
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In the paper the sequential nonlinear mapping has been investigated in order to reveal its features. The method was investigated by a plenty of experiments using various sorts of data. For illustrations there are presented results using “marginal” data: the first data gives the smallest mapping error, and the other data gives the largest one. The sequential nonlinear mapping has been investigated according ability to differ the data groups (clustering) when at the beginning the number of groups is taken to be less than really exists. It was showed that the sequential nonlinear mapping differs the groups of data well even though the number of them is taken to be less by one than really exists. The experiments show that the factor for correction co-ordinates on the plane for the sequential nonlinear mapping can be taken in the range from 0.25 to 0.75. Mapping errors depend on both the sort of initial conditions and the nature of data.