Although decision tree classifiers have achieved success in many
domains, we have not seen a public domain package that can handle
large classification problems that require a large number of classes
and attributes. The goal of this project is to develop a decision tree
package free to the public that can handle these problems.
This is the first beta release of the decision tree package developed at ISIP. The package contains a suit of well-known decision tree algorithms in a common framework. The code is written in C++ following the object-oriented data-driven paradigm. The current package features:
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