mvpa2.mappers.procrustean.ProcrusteanMapper¶
- class mvpa2.mappers.procrustean.ProcrusteanMapper(scaling=True, reflection=True, reduction=True, oblique=False, oblique_rcond=-1, svd='numpy', **kwargs)¶
Mapper to project from one space to another using Procrustean transformation (shift + scaling + rotation)
Notes
Available conditional attributes:
- calling_time+: Time (in seconds) it took to call the node
- raw_results: Computed results before invoking postproc. Stored only if postproc is not None.
- training_time+: Time (in seconds) it took to train the learner
(Conditional attributes enabled by default suffixed with +)
Initialize the ProcrusteanMapper
Parameters : scaling : bool
Scale data for the transformation (no longer rigid body transformation)
reflection : bool
Allow for the data to be reflected (so it might not be a rotation). Effective only for non-oblique transformations
reduction : bool
If true, it is allowed to map into lower-dimensional space. Forward transformation might be suboptimal then and reverse transformation might not recover all original variance
oblique : bool
Either to allow non-orthogonal transformation – might heavily overfit the data if there is less samples than dimensions. Use oblique_rcond.
oblique_rcond : float
Cutoff for ‘small’ singular values to regularize the inverse. See lstsq for more information.
svd : string (numpy, scipy, dgesvd), optional
Implementation of SVD to use. dgesvd requires ctypes to be available.
enable_ca : None or list of str
Names of the conditional attributes which should be enabled in addition to the default ones
disable_ca : None or list of str
Names of the conditional attributes which should be disabled
demean : bool
Either data should be demeaned while computing projections and applied back while doing reverse()
