The following module was proposed for inclusion in the Module List:
modid: Algorithm::DecisionTree
DSLIP: bdpOp
description: Decision-tree based classification of data
userid: AVIKAK (Avinash Kak)
chapterid: 6 (Data_Type_Utilities)
communities:
mailinglists, newsgroups
similar:
AI::DecisionTree
rationale:
The Algorithm::DecisionTree is a full-blown implementation of the
class entropy-based approach to decision tree construction.
From the standpoint of its practical usefulness, the module
generates all applicable class labels for a new data sample if so
warranted by the amount of information (and its nature) in the
training data set. In other words, if the class distributions are
overlapping in the underlying feature space, the decision tree
classifier will show you all the class lables for a datapoint that
falls in the overlap region.
The implementation is designed to work with large datasets and has
an interface that I believe is convenient to use for diskfile based
training datasets. In other words, the implmentation is NOT a toy
example. The implementation also includes facilities for creating
large training datasets to experiment with decision-tree based
approach to data classification.
enteredby: AVIKAK (Avinash Kak)
enteredon: Mon Dec 13 05:03:31 2010 GMT
The resulting entry would be:
Algorithm::
::DecisionTree bdpOp Decision-tree based classification of data AVIKAK
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