The algorithm used
Yet another Decision Tree builder
. The adjustable parameter is the minimum number of
instances that is required for a node to be split (default: 10, larger values result in a
more general tree, smaller values may lead to overfitting).
As a result, confusion matrices on the training data and on the test data are displayed,
along with the decision tree.
A visual representation of the decision tree is built from YaDT's XML output via XSLT,
the different nodes are colored according to the ratio of F and M instances covered (100% F is red,
100% M is blue), branches can be opened and closed for inspection.