association, apriori and frequent itemsets

Hi all,

I need to generate association rules from a data set. this data set is
really huge (~5 million entries), with 40+ attributes, and these
attributes have values that are either nominal or numerical. I've
tried out several softwares, but I still can't find one that works
with my data set.

I've tried weka, but it does not accept numerical data. other then
that, its a pretty good software. I've also tried ARMADA, but it only
accepts data of string type.

I've also tried Christian Borgelt's apriori program but the attributes
are not taken into account. I could modify my data so that it is
possible to distinguish the attribute [e.g. if attribute duration has
values such as 0, 124, etc, i could change them to d_0, d_124, etc, to
show that these values belong to attribute duration.] However, this
isn't very efficient because i have 5 million entries and i would have
to manually change everyone of them.

I've tried Christian Borgelt's eclat program to generate frequent set
and the attributes are also not taken into account.

Can anyone recommend any other software? (i need them to be free
because i'm just a poor student doing research). Or if anyone has a
solution using the software mentioned above, please email me and throw
me a lifeline.

Any help is deeply appreciated. Thanks!

meiyi

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