Algorithm::DecisionTree is a Perl module for constructing a
decision tree from multidimensional training data and for
using the decision tree thus induced for classifying data.
The decision tree is constructed from the training data
supplied through a disk file.

If your training data includes numeric features, you must
supply the data through a CSV file.  On the other hand, if
you training data has only symbolic features, you can use
either a CSV file or a `.dat' files of the sort used for
training in the previous versions of this module.

From the standpoint of practical usefulness, note that the
classifier carries out soft classifications.  That is, if
the class distributions are overlapping in the underlying
feature space and a test sample falls in the overlap region,
the classifier will generate all applicable class labels for
the test data sample, along with the probability of each
class label.

For installation, do the usual

    perl Makefile.PL
    make
    make test
    make install

if you have root access.  If not, 

    perl Makefile.PL prefix=/some/other/directory/
    make
    make test
    make install

Contact:

Avinash Kak  

email: kak@purdue.edu

Please place the string "DecisionTree" in the subject line
if you wish to write to the author.  Any feedback regarding
this module would be highly appreciated.