Problems finding best length using cross validation in parallel

[AniekMarkus]

Running EXPLORE for mix_4.arff with settings:

PartitionMethod=CROSS_VALIDATION
StartRulelength=1
EndRulelength=5
LearnRatio=0.7
NumberofPartitions=3
Subsumption=no
BranchBound=no
Parallel=yes (fo 'no' EXPLORE successfully completes)
ParallelMethod=ONE
BinaryReduction=yes

Sometimes gives error messages after 1 or 2 partitions (e.g. the one below) and sometimes successfully completes:
libc++abi: terminating due to uncaught exception of type std::length_error: vector Process finished with exit code 134 (interrupted by signal 6: SIGABRT)

In addition: when re-training model with full train set (learn + validate), the functions induce() etc. not yet available in parallel.