Sparsity and smoothness via the fused lasso
The lasso penalizes a least squares regression by the sum of the absolute values ("L" 1-norm) of the coefficients. The form of this penalty encourages sparse solutions (with many coefficients equal to 0). We propose the 'fused lasso', a generalization that is designed for problems with features that can be ordered in some meaningful way. The fused lasso penalizes the "L" 1-norm of both the coefficients and their successive differences. Thus it encourages sparsity of the coefficients and also sparsity of their differences-i.e. local constancy of the coefficient profile. The fused lasso is especially useful when the number of features "p" is much greater than "N", the sample size. The technique is also extended to the 'hinge' loss function that underlies the support vector classifier. We illustrate the methods on examples from protein mass spectroscopy and gene expression data. Copyright 2005 Royal Statistical Society.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 67 (2005)
Issue (Month): 1 ()
|Contact details of provider:|| Postal: |
Web page: http://wileyonlinelibrary.com/journal/rssbEmail:
More information through EDIRC
|Order Information:||Web: http://ordering.onlinelibrary.wiley.com/subs.asp?ref=1467-9868&doi=10.1111/(ISSN)1467-9868|
When requesting a correction, please mention this item's handle: RePEc:bla:jorssb:v:67:y:2005:i:1:p:91-108. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wiley-Blackwell Digital Licensing)or (Christopher F. Baum)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.