Limiting Decision Tree branching factor

Unknown
Unknown
edited November 5 in Community Q&A
Hi everybody ,

I have a dataset with 5 attributes , one is nominal and it has large number of possible values (~5000 values) , I want to train a decision tree on this dataset but the problem is that when I include this feature , the branching factor for this attribute is very large and so model doesn't in the memory (I use 74 GB of main memory) , my dataset has about 620 K instances (rows) ,


Is it possible to put a limit on branching factor for this attribute ?

Thanks ,
Arian
Tagged:

Answers

  • MariusHelf
    MariusHelf New Altair Community Member
    Hi Arian,

    no, you can't limit the branching factor - for each nominal value a single branch will be created. But probably an attribute with that many features is probably not the best choice anyway. But tell me, are the values a fixed set, or is possible that new data contains different, new values? In that case the example is useless anyways.

    Best regards,
    Marius

Categories