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|Table of Contents Multivariate Data Basic Knowledge Structure of Measured Data|
|See also: data, linear vs. nonlinear models|
In order to apply any method of data analysis, you have to be knowledgable about the structure of your data. Depending on the kind of analysis (classification or calibration), you should look for several aspects of the data set.
In the case of classification problems, there are basically three cases to be distinguished:
In the case of calibration problems, there are two aspects which should be considered prior to building a model:
Again, this decision is not easily made and is even more complicated
by noise in the data. In the case of extensive noise, a possible non-linear
relationship is often covered by the noise, thus making it impossible to
create a non-linear model.
Last Update: 2006-Jšn-17