Combiner mappings

(This topic is mainly important for PRTools programmers designing mappings)

Mappings of the combiner type operate on other mappings and not directly on data. They are used to modify the properties of a given mapping. An example is classc which converts a classifier that outputs class densities to one that results in posterior probabilities. In addition there are the fixed combiners designed of combining set of classifiers that are grouped in a stacked (i.e. in the same vector space) or parallel (in different vector spaces) way.

There are not many checks programmed for combiners. It is easy to apply a wrong mapping to a combiner. Usually only after applying data to mappings errors will be generated. This may confuse users as these errors are not always directly meaningful.

The main rules for combining  a combiner mapping V with arbitrary fixed and trained mappings W, untrained mappings U and trained mappings T are

elements: datasets datafiles cells and doubles mappings classifiers mapping types.
operations: datasets datafiles cells and doubles mappings classifiers stacked parallel sequential dyadic.
user commands: datasets representation classifiers evaluation clustering examples support routines.
introductory examples: Introduction Scatterplots Datasets Datafiles Mappings Classifiers Evaluation Learning curves Feature curves Dimension reduction Combining classifiers Dissimilarities.
advanced examples.