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.