Stacked combining

By stacked combining, sets of mappings are combined that operate from the same input space into different output spaces. The resulting mapping concatenates these output spaces. The combining operator is the horizontal concatenation. So if we have three mappings W1, W2 and W3, they are combined by

    W = [W1 W2 W3];

which means that if a dataset A is mapped by W it results in the concatenation of resulting datasets:

    B = A*W; 
    B = [A*W1 A*W2 A*W3];


Stacked combining can also be applied to untrained mappings. In that case a set of untrained base mappings  U1U2... are trained separately, resulting in W1W2.... These constitute a new, now trained, combined mapping.

    U = [U1 U2 U3];  % concatenation of untrained mappings
    W = A*U;         % training, results in W = [A*U1 A*U2 A*U3] = [W1 W2 W3]



operations: basic, datasets, datafiles, mappings, classifiers, stacked, parallel, sequential, dyadic
commands: datasets, representation , classifiers, evaluation, clustering and regression, examples, support

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