Oblivious Decision Trees, Graphs, and Top-Down Pruning
نویسندگان
چکیده
We describe a supervised learning algorithm, EODG that uses mutual information to build an oblivious decision tree The tree is then converted to an Oblivious read-Onre Decision Graph (OODG) b\ merging nodes at the same level of the tree For domains that art appropriate for both decision trees and OODGs, per formance is approximately the same aS THAT of C45 ), but the number of nodes in the OODG is much smalle r The merging phase that converts the oblivious decision tree to an OODG provides a new way of dealing with the replication problem and a new pruning mechanism that works lop down starting from tin root The pruning mechanism is well suited for finding symmetries and aids in recovering from splits on irrelevant features that mav happen during the tree consLrm tion
منابع مشابه
Oblivious Decision Trees , Graphs , and Top - Down
We describe a supervised learning algorithm, EODG, that uses mutual information to build an oblivious decision tree. The tree is then converted to an Oblivious read-Once Decision Graph (OODG) by merging nodes at the same level of the tree. For domains that are appropriate for both decision trees and OODGs, performance is approximately the same as that of C4.5, but the number of nodes in the OOD...
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