I'd use Random Forest. It will give you better generalizability. There
are also a number of things you can do with RF that allows to train on
samples of the massive data set and then just average over the resulting
models...
Thanks,
Ron
On 07/21/2015 02:17 PM, Olivier Girardot wrote:
depends on your data and I guess the time/performance goals you have
for both training/prediction, but for a quick answer : yes :)
2015-07-21 11:22 GMT+02:00 Chintan Bhatt
<chintanbhatt...@charusat.ac.in <mailto:chintanbhatt...@charusat.ac.in>>:
Which classifier can be useful for mining massive datasets in spark?
Decision Tree can be good choice as per scalability?
--
CHINTAN BHATT <http://in.linkedin.com/pub/chintan-bhatt/22/b31/336/>
Assistant Professor,
U & P U Patel Department of Computer Engineering,
Chandubhai S. Patel Institute of Technology,
Charotar University of Science And Technology (CHARUSAT),
Changa-388421, Gujarat, INDIA.
http://www.charusat.ac.in <http://www.charusat.ac.in/>
_Personal Website_: https://sites.google.com/a/ecchanga.ac.in/chintan/
