
 Description:
Correlative Matrix Mapping (CMM): If X is a realvalued data matrix (row data vectors) and L the matrix with associated information (row 'label' vectors), then a linear mapping V is computed such that their distance matrices D_X^V and D_L, respectively, are mapped to provide maximum correlation r(D_X^V, D_L) = max. The matrix entries (D_X^V)_ij = sqrt( (x^ix^j) * V * V' * (x^ix^j) ) describe the adaptive (Mahalanobislike) matrix distance between data vectors x^i and x^j with V being optimized according to the maximum correlation mapping criterion induced by D_L.
Correlative Matrix Mapping (CMM) was formerly (before a naming conflict was recognized) known as Multivariate Subspace Regression (MSR) by Strickert, Soto, Vazquez (http://www.dice.ucl.ac.be/esann/proceedings/papers.php?ann=2010).
CMM supersedes Supervised Attribute Relevance Detection using Cross Comparisons (SARDUX) by Strickert, Soto, Vazquez (http://dig.ipkgatersleben.de/sardux/sardux.html)
The CMM approach is related to canonical correlation analysis, but transforms only the data space to match the wellknown static 'label' distance relationships.
 Changes to previous version:
Tue Jul 5 14:40:03 CEST 2011  Bugfixes and cleanups
 single precision data affected pinv(). Now fairer using double precision.
 early stopping did not work properly; now fixed
 Hessian update mode globally controlled via hessmode, 'lbfgs' / 'bfgs'
 distmat.m corrected for rounding problems and extended to distmat(X,Y)
 replaced files: corv.m + corvgrad.m > corvg.m
 removed unused files: corrmat.m, splitdata.m, traforankapply.m
 BibTeX Entry: Download
 Corresponding Paper BibTeX Entry: Download
 Supported Operating Systems: Platform Independent
 Data Formats: Matlab
 Tags: Lda, Dimensionality Reduction, Supervised Learning, Linear Discriminant Analysis, Association Mapping, Canonical Correlation Analysis, Cca, Linear Model
 Archive: download here
Other available revisons

Version Changelog Date 1.1 Tue Jul 5 14:40:03 CEST 2011  Bugfixes and cleanups
 single precision data affected pinv(). Now fairer using double precision.
 early stopping did not work properly; now fixed
 Hessian update mode globally controlled via hessmode, 'lbfgs' / 'bfgs'
 distmat.m corrected for rounding problems and extended to distmat(X,Y)
 replaced files: corv.m + corvgrad.m > corvg.m
 removed unused files: corrmat.m, splitdata.m, traforankapply.m
July 5, 2011, 15:15:21 1.0 Initial Announcement on mloss.org.
February 2, 2011, 11:48:07
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