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Best PC configuration for Rapid-I?
Hi,
can we please discuss, which will be the best configuration to buy to speed up Rapid-I work with large example sets?
I recently use a Pentium4 - 3.0Ghz PC with 1,5Gb RAM and fast SATA HDD on WinXP.
My task is to extract rules via the RuleLearner for a large dataset (>65000 examples) :-( I do not want wight the set or reduce the # of the examples and had run a test, which i waited for 24h and i founded still working.
So can anyone please explain: Will a Core QUAD CPU with 4GB RAM do it much faster so that it will be worht to buy it? Is Rapid ready to use those HT multitasking skills or it will be better to buy 8GB RAN for the old configuaration?
Thanks and happy new year
can we please discuss, which will be the best configuration to buy to speed up Rapid-I work with large example sets?
I recently use a Pentium4 - 3.0Ghz PC with 1,5Gb RAM and fast SATA HDD on WinXP.
My task is to extract rules via the RuleLearner for a large dataset (>65000 examples) :-( I do not want wight the set or reduce the # of the examples and had run a test, which i waited for 24h and i founded still working.
So can anyone please explain: Will a Core QUAD CPU with 4GB RAM do it much faster so that it will be worht to buy it? Is Rapid ready to use those HT multitasking skills or it will be better to buy 8GB RAN for the old configuaration?
Thanks and happy new year
0
Answers
as haddoc already said: Multiple threads cannot be automatically supported since learning tasks are highly interdependet on previous results. But there are some learner as the rule learner providing some parallelizable parts. But this is only included in the enterprise edition.
So if you want to have a fast computer for community edition buy a high performance dual core with fast ram. It cannot be wrong to buy lots of RAM, but if the problems fits into your 1.5 GB, 2 GB should do the work, too. If you want to use more than 3 GBs or RAM you have to use a 64bit operating system.
I personally would rather tune my process setup, since a new (single thread) computer will not speed up the computation more than twice. While changing the setup might do the trick. Perhabs the rule learner is somehow caught in the very noisy remaining examples or overfits misserably. The resulting rules then will not tell you anything and hence the generation might be stopped before.
If you don't need the rules as human readable model, you might change the learning algorithm.
Another important fact on the rule learner is, that the number of attributes has heavy impact on the runtime.
Greetings,
Sebastian
I will improve the RAM speed and size :-)