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Mapper using a projection matrix to transform the data.
This class cannot be used directly. Sub-classes have to implement the _train() method, which has to compute the projection matrix given a dataset (see _train() docstring for more information).
Once the projection matrix is available, this class provides functionality to perform forward and backwards mapping of data, the latter using the hermitian (conjugate) transpose of the projection matrix. Additionally, ProjectionMapper supports optional (but done by default) demeaning of the data and selection of arbitrary component (i.e. columns of the projection matrix) of the projection.
Forward and back-projection matrices (a.k.a. projection and reconstruction) are available via the proj and recon properties. the latter only after it has been computed (after first call to reverse).
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Inherited from Inherited from |
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__doc__ = enhancedDocString('ProjectionMapper', locals(), Mapper)
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proj = property(fget= lambda self: self._proj, doc= "Projectio
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recon = property(fget= lambda self: self._recon, doc= "Backpro
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Inherited from |
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Worker method. Needs to be implemented by subclass. This method has to train the mapper and store the resulting transformation matrix in self._proj. |
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proj
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recon
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