question about learning algorithms

I have a simple learning problem ("simple" in the sense that it is easy to understand!).

Consider the following website of house plans:

http://www.planhouse.com/default.aspx

You will notice that the plans are categorized into sets. For any single plan, there is a list of features. For example, check out the "plan details" (in green) near the middle of this page:

http://www.planhouse.com/plan.aspx?id=2361

Every plan comes with a set of details like that.

Now, I wanted to see whether I could use Weka to correctly classify plans. So, I copied down 30 sets of plan details from that website: 15 in one category and 15 in another. I then used the Bayesian Network algorithm to attempt to classify them. No luck. It gave me about a 50% success rate (no better than random).

The reason I chose Bayesian learning is simply because I won't have a large dataset. Now, I will increase the size of my dataset to see if that makes a difference, but I was wondering if anyone out there has any suggestions as to what I should be looking at?

Thanks!

J.