From: michael.madden@nuigalway.ie   
      
   [Re-posting: was not delivered first time]   
      
   David Tian wrote:   
   > Hi,   
   >   
   > I have installed the executable of MLC++ utilities. I want to run c4.5   
   > on iris dataset. I have read the utilities manual and also did the   
   > settings described in the README.NT file for it, but I am still not   
   > sure how to run it.   
   > Would anyone provide with me an example command please?   
   >   
   > Regards,   
   >   
   > David   
   >   
      
   Hi David;   
      
   Under Windows, instead of typing "setenv DATAFILE iris" (as in the   
   utilities manual), you must type "set DATAFILE=iris".   
      
   Also, as well as installing the MLC++ executables (inducer.exe,   
   discretize.exe, etc.) you may need to install other packages. C4.5, for   
   example, is not built into MLC; it is an external package that you will   
   need to download and install so that MLC can find it. Another useful   
   package you may need is the 'dotty' tools for displaying graphs, as   
   mentioned in the Utilites manual.   
      
   Here is a simple example of running MLC++, using ID3 rather than C4.5,   
   as ID3 is a regular inducer rather than an external/base inducer. This   
   example assumes that the directory with the executables of the MLC++   
   utilities are on your path (type PATH in the Command Prompt window to   
   list the path). For simplicity, CD to the directory containing the data   
   files, which must be called iris.data, iris.test and iris.names. The   
   commands are:   
      
   set DATAFILE=iris   
   set INDUCER=ID3   
   set DISP_CONFUSION_MAT=yes   
   inducer   
      
   This will produce the output shown for Example 1 in the Utilities manual.   
      
   If you have downloaded C4.5 and added its BIN directory to your path,   
   you can run it on the iris dataset as follows:   
      
   set DATAFILE=iris   
   set INDUCER=C4.5   
   inducer   
      
   Hope this helps,   
   Michael.   
      
      
   PS: Most people these days prefer to use WEKA, which has an intuitive   
   user interface, is more easily extended, and has implementations of a   
   wide and growing range of algorithms.   
      
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