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pymining's Issues

mine_assoc_rules: Incorrect handling of the min_confidence parameter

When running the min_assoc_rules function on a dataset, the results include the following:
(frozenset(['a']), frozenset(['b', 'c']), 75, 0.5102040816326531),
(frozenset(['a', 'b']), frozenset(['c']), 75, 0.9375),
(frozenset(['a', 'c']), frozenset(['b']), 75, 0.8064516129032258),

However, the last 2 are produced only if min_confidence=0.5. Instead, they should appear if min_confidence>0.8.

osx-64 anaconda package

Please create an osx-64 anaconda package.
Currently it only has a linux-64 one.

I built it locally and installed it with
conda skeleton pypi pymining
conda build pymining
conda install ~/anaconda/conda-bld/osx-64/pymining-0.2-py27_0.tar.bz2

seems min_support does not work well as expected

report = itemmining.relim(relim_input, min_support=4)

here is dataset I used to test transactions = (('1','14043','6686','8302','8298'),('1','14043','6686','8298','8302'),('1','14043','6686','8302','8298'),('1','14043','6686','8298','8302'),('1','14043','8302','6686','8298'),('1','14043','6686','8302','8298'),('1','14043','6686','8302','8298'),('1','14043','6686','8298','8302'),('1','14043','8302','8298','6686'),('1','14043','6686','8298','8302'),('1','14043','6686','8298','8302'),('1','14043','6686','8298','8302'),('1','14043','6686','8298','8302'),('1','14043','6686','8298','8302'),('1','14043','6686','8298','8302'),('1','14043','6686','8302','8298'),('1','14043','6686','8302','8298'),('1','14043','6686','8302','8298'),('1','14043','8298','8302','6686'),('1','14043','6686','8302','8298'),('1','14043','6686','8302','8298'),('1','14043','6686','8298','8302'),('1','14043','6686','8298','8302'),('1','14043','8302','8298','6686'),('1','14043','6686','8298','8302'),('1','14043','6686','8298','8302'),('1','14043','6686','8298','8302'),('1','14043','6686','8298','8302'),('1','14043','8298','8302','6686'),('1','14043','6686','8298','8302'),('1','14043','6686','8298','8302'),('1','14043','6686','8302','8298'),('1','14043','6686','8302','8298'),('1','14043','6686','8298','8302'),('1','14043','6686','8302','8298'),('1','14043','8302','8298','6686'),('1','14043','8302','8298','6686'),('1','14043','6686','8302','8298'),('1','14043','8302','6686','8298'),('14043','1','6686','8302','8298'),('1','14043','6686','8298','8302'),('1','14043','6686','8302','8298'),('1','14043','8302','6686','8298'),('1','14043','6686','8302','8298'),('8298','14043','6686','8302','1'),('1','14043','8302','6686','8298'),('1','14043','6686','8302','8298'),('1','14043','8298','6686','8302'),('1','14043','6686','8298','8302'),('1','14043','6686','8302','8298'),('1','14043','6686','8298','8302'),('1','14043','8298','8302','6686'),('1','14043','6686','8298','8302'),('1','14043','6686','8302','8298'),('1','14043','8302','8298','6686'),('1','14043','8298','8302','6686'),('6686','1','8298','8302','14043'),('1','14043','8302','8298','6686'),('1','14043','6686','8298','8302'),('1','14043','6686','8298','8302'),('1','8302','14043','6686','8298'),('1','8298','14043','6686','8302'),('1','8298','8302','14043','6686'),('1','8302','14043','8298','6686'),('1','8298','14043','6686','8302'),('1','8298','8302','14043','6686'),('1','8298','8302','14043','6686'),('1','8302','14043','6686','8298'),('1','8298','8302','14043','6686'),('1','8298','8302','14043','6686'),('1','8298','8302','14043','6686'),('6686','1','14043','8298','8302'),('1','8298','8302','14043','6686'),('1','6686','14043','8302','8298'),('1','8302','14043','6686','8298'),('1','8302','8298','14043','6686'),('1','8302','14043','8298','6686'),('14043','6686','1','8298','8302'),('1','8302','14043','6686','8298'),('1','8302','8298','14043','6686'),('1','8302','8298','14043','6686'),('1','8298','8302','14043','6686'),('8298','8302','1','14043','6686'),('1','8302','14043','6686','8298'))

out put
{frozenset(['1', '8298', '14043']): 84, frozenset(['8298', '8302', '6686', '14043']): 84, frozenset(['1', '8298', '8302', '6686']): 84, frozenset(['8298', '14043']): 84, frozenset(['8298']): 84, frozenset(['8302', '14043']): 84, frozenset(['8302', '6686']): 84, frozenset(['6686', '14043']): 84, frozenset(['8298', '6686', '14043']): 84, frozenset(['1', '6686']): 84, frozenset(['1', '14043']): 84, frozenset(['1', '8298', '8302']): 84, frozenset(['1', '6686', '14043']): 84, frozenset(['1', '8298', '6686', '14043']): 84, frozenset(['8298', '6686']): 84, frozenset(['8302', '6686', '14043']): 84, frozenset(['1']): 84, frozenset(['1', '8298']): 84, frozenset(['1', '8298', '8302', '6686', '14043']): 84, frozenset(['8298', '8302', '14043']): 84, frozenset(['1', '8302']): 84, frozenset(['1', '8298', '6686']): 84, frozenset(['1', '8302', '6686']): 84, frozenset(['1', '8298', '8302', '14043']): 84, frozenset(['6686']): 84, frozenset(['14043']): 84, frozenset(['1', '8302', '14043']): 84, frozenset(['8298', '8302']): 84, frozenset(['8302']): 84, frozenset(['1', '8302', '6686', '14043']): 84, frozenset(['8298', '8302', '6686']): 84}

code
from pymining import itemmining

cluster07_transactions = (('1','14043','6686','8302','8298'),('1','14043','6686','8298','8302'),('1','14043','6686','8302','8298'),('1','14043','6686','8298','8302'),('1','14043','8302','6686','8298'),('1','14043','6686','8302','8298'),('1','14043','6686','8302','8298'),('1','14043','6686','8298','8302'),('1','14043','8302','8298','6686'),('1','14043','6686','8298','8302'),('1','14043','6686','8298','8302'),('1','14043','6686','8298','8302'),('1','14043','6686','8298','8302'),('1','14043','6686','8298','8302'),('1','14043','6686','8298','8302'),('1','14043','6686','8302','8298'),('1','14043','6686','8302','8298'),('1','14043','6686','8302','8298'),('1','14043','8298','8302','6686'),('1','14043','6686','8302','8298'),('1','14043','6686','8302','8298'),('1','14043','6686','8298','8302'),('1','14043','6686','8298','8302'),('1','14043','8302','8298','6686'),('1','14043','6686','8298','8302'),('1','14043','6686','8298','8302'),('1','14043','6686','8298','8302'),('1','14043','6686','8298','8302'),('1','14043','8298','8302','6686'),('1','14043','6686','8298','8302'),('1','14043','6686','8298','8302'),('1','14043','6686','8302','8298'),('1','14043','6686','8302','8298'),('1','14043','6686','8298','8302'),('1','14043','6686','8302','8298'),('1','14043','8302','8298','6686'),('1','14043','8302','8298','6686'),('1','14043','6686','8302','8298'),('1','14043','8302','6686','8298'),('14043','1','6686','8302','8298'),('1','14043','6686','8298','8302'),('1','14043','6686','8302','8298'),('1','14043','8302','6686','8298'),('1','14043','6686','8302','8298'),('8298','14043','6686','8302','1'),('1','14043','8302','6686','8298'),('1','14043','6686','8302','8298'),('1','14043','8298','6686','8302'),('1','14043','6686','8298','8302'),('1','14043','6686','8302','8298'),('1','14043','6686','8298','8302'),('1','14043','8298','8302','6686'),('1','14043','6686','8298','8302'),('1','14043','6686','8302','8298'),('1','14043','8302','8298','6686'),('1','14043','8298','8302','6686'),('6686','1','8298','8302','14043'),('1','14043','8302','8298','6686'),('1','14043','6686','8298','8302'),('1','14043','6686','8298','8302'),('1','8302','14043','6686','8298'),('1','8298','14043','6686','8302'),('1','8298','8302','14043','6686'),('1','8302','14043','8298','6686'),('1','8298','14043','6686','8302'),('1','8298','8302','14043','6686'),('1','8298','8302','14043','6686'),('1','8302','14043','6686','8298'),('1','8298','8302','14043','6686'),('1','8298','8302','14043','6686'),('1','8298','8302','14043','6686'),('6686','1','14043','8298','8302'),('1','8298','8302','14043','6686'),('1','6686','14043','8302','8298'),('1','8302','14043','6686','8298'),('1','8302','8298','14043','6686'),('1','8302','14043','8298','6686'),('14043','6686','1','8298','8302'),('1','8302','14043','6686','8298'),('1','8302','8298','14043','6686'),('1','8302','8298','14043','6686'),('1','8298','8302','14043','6686'),('8298','8302','1','14043','6686'),('1','8302','14043','6686','8298'))
relim_input = itemmining.get_relim_input(cluster07_transactions)
report = itemmining.relim(relim_input, min_support=4)
print (report)

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