OK Thanks
I'll try both and I'll tell you how it works :)
Loic
Le 12.09.2011 22:24, Ted Dunning a écrit :
SVM is reasonable.
SGD with hand-tuning of the learning parameters may work.
With so little training data, you will have a difficult assessing whether
your system is working.
Sometimes, you can rephrase your problem so that all of your training data
across many situations can be pooled together. There is a nice paper on
google priority mail about just such an example where Google used
meta-features so that they could train a few models across all users
On Mon, Sep 12, 2011 at 6:52 AM, Loic Descotte<[email protected]>wrote:
My classification problem is very similar to the "20 newsgroups" example.
But I don't have the possibility to use a large quantity of data for
training.
...
I'd like to try with 10 examples by category (with 2 or 3 category),
choosing good examples with the more frequent keywords to be sure that the
learning phase will be efficient.
Can it be relevant with so little data ?
