Best learning algorithm to make a decision tree in java?

Question

I have a datasets with information like age, city, age of children, ... and a result (confirm, accept).

To help modelisation of "workflow", I want to create automatically a decision tree based on previous datasets.

I have take a look at http://en.wikipedia.org/wiki/Decision_tree_learning and I know that the problem is clearly not obvious.

I just want to have advice on some algorithm or some libs on this subject what can help me in the contruction of a decision tree based on samples.

Answer 1

You should take a look at Weka, a free Java-based supervised learning suite.

After converting your data into Weka's simple text-based .arff format, you should be able to use the GUI or command-line interface to train and test a variety of different classifiers on that data, including:

• decision trees
• neural networks
• rule-based systems
• support vector machines (SVMs)
• various types of regression

Experimenting with this interface should allow you to easily try different classifiers and training parameters to determine which ones perform the best on your data.

You can also use an API to integrate Weka into your own source code.

Answer 2

If you want to compare performance of different types of decision trees from Weka, see benchmark results collected in TunedIT.org:

http://tunedit.org/results?d=UCI&a=Weka*tree.

Play with drop-down lists and name patterns of algorithms/datasets to choose which results should be presented.