Solutions to frequent problems

The experiment fails and I cannot figure out why?

If something goes wrong, always carefully look into the log file. If there is no hint what went wrong, repeat the experiment with the added options -d and -lad. This will create a huge logfile, since all the output of all learning algorithms will be included, but usually contains the crucial information about what went wrong. Some things to check for: are all programs that are needed from the interface scripts in the binary search path? The helper programs too? Is the directory used to store temporary files on a device that has enough free space to hold all the temporary files? Are there leftover temporary files from earlier runs that clobber up space?

A CPU timeout was specified, but the algorithms run much longer?

On some systems - mainly Windows - the CPU limitation mechanism does not work. Unfortunately there is no solution for this as of now.

A CPU timeout was specified, but the algorithm seems to never stop?

Apart from the cause given in the previous problem, it is also possible that the learning algorithm or some other algorithm that gets called (indirectly via interface scripts) from run_exp is waiting for input from the standard input stream. In that case, the algorithm is halted, does not consume CPU time and thus, never stops. One reason for this behaviour could be that a licensed learning algorithm is requesting a license code.

It seems for some of the folds there are empty train/test files?

If the database is very small and there are many different class labels, the shuffle program will not be able to do stratification correctly without leaving some of the files empty. In that case, simply turn off stratification (option -start 0).