Large Data Handeling
sangihi
New Altair Community Member
Hi,
I'm trying to classify huge data (about 500K rows) using Decision Trees in RapidMiner.
Unfortunately, the GUI gives me not enough memory even for 50K data.
Since C4.5 is able to learn the whole data instance by instance, Is it possible to "stream" data so it does not require the whole data in memory?
I'm trying to classify huge data (about 500K rows) using Decision Trees in RapidMiner.
Unfortunately, the GUI gives me not enough memory even for 50K data.
Since C4.5 is able to learn the whole data instance by instance, Is it possible to "stream" data so it does not require the whole data in memory?
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Answers
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1) RM manage memory very efficiently so if you are able to store the dataset in the memory, you shouldn't have any problems
2) If you have a problem then use database to store the data
3) The main problem is that the decision tree (DT) build in RM is very crappy. My advice - don't use it, use J48 from weka plugin instead, or use other models kNN, Naive Bayes etc.0