I have a compilation problem on FC2, 2xXeon box. The following dialogue output from the end of the compilation illustrates: [very large snipping sound ...] * DONE (cluster) begin installing recommended package foreign make[2]: *** [foreign.ts] Error 1 make[2]: Leaving directory `/usr/src/redhat/SOURCES/R-2.0.1/src/library/Recommended' make[1]: *** [recommended-packages] Error 2 make[1]: Leaving directory `/usr/src/redhat/SOURCES/R-2.0.1/src/library/Recommended' make: *** [stamp-recommended] Error 2 There are no error messages in the configuration step - it only says I can't prepare DVI or PDF versions of the manual. Fair enough - info will do quite nicely. It seems there is a problem trying to install package 'foreign' and perhaps this leads to the other two errors. The compiler suite is 3.3.3-7. I have the full config.out and error.out files stored for inspection if required. Nothing appears to be installed. Any clues? TIA John John Logsdon "Try to make things as simple Quantex Research Ltd, Manchester UK as possible but not simpler" j.logsdon at quantex-research.com a.einstein at relativity.org +44(0)161 445 4951/G:+44(0)7717758675 www.quantex-research.com
On Wed, 1 Dec 2004, John Logsdon wrote:> I have a compilation problem on FC2, 2xXeon box. > > The following dialogue output from the end of the compilation illustrates: > > [very large snipping sound ...] > * DONE (cluster) > begin installing recommended package foreign > make[2]: *** [foreign.ts] Error 1 > make[2]: Leaving directory > `/usr/src/redhat/SOURCES/R-2.0.1/src/library/Recommended'Take a look at the file foreign.out in that directory. (R-devel does this better, by cat-ing the file at that point.) -- Brian D. Ripley, ripley at stats.ox.ac.uk Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595
Hi, I am using SVM from e1071 package. I am using RBF kernel. I would like to know how I can get "d", the perpendicular distance from a datapoint to the hyperplane, that SVM calculates in higher dimensional space to classify it. Although, this is not something that people usually use, but for my case I like to do something with that distance. Does anybody have any idea how to get it? Thanks. Raj