mloss.org RegLin Posterior Regularization of Linear Mappingshttp://mloss.orgUpdates and additions to RegLin Posterior Regularization of Linear MappingsenWed, 23 May 2012 10:31:34 -0000RegLin Posterior Regularization of Linear Mappings 1.1http://mloss.org/software/view/339/<html><p>Linear mappings are omnipresent in data processing analysis ranging from regression to distance metric learning. The interpretation of coefficients from under-determined mappings raises an unexpected challenge when the original modeling goal does not impose regularization. The RegLin package implements a general posterior regularization strategy for inducing unique results. </p> <p>The benefits are: &lt;1&gt; reflection of data properties such as smoothness in spectrum profiles, &lt;2&gt; easier interpretation of regularized mapping coefficients, and &lt;3&gt; potentially improved mapping quality for unseen test data, i.e. better generalization. </p> <p>The package also includes a function for standardizing the mapping coefficient vectors by projection to eigenvectors, and an attribute assessment strategy based on sensitivity analysis of the coefficient vectors - these two methods do not require under-determined systems. </p> <p>The package contains example cases using pinv() and an external linear model (correlative matrix mapping CMM @ mloss.org) for colon cancer gene expression data and for a data base containing near-infrared spectral profiles. See Readme.txt contained in the package. </p></html>marc strickertWed, 23 May 2012 10:31:34 -0000http://mloss.org/software/rss/comments/339http://mloss.org/software/view/339/regularizationlinear model