Decision tree classification with bounded number of errors


Oblivious decision trees are decision trees where every node in the same level is associated with the same attribute. These trees have been studied in the context of feature selection. In this paper, we study the problem of constructing an oblivious decision tree that incurs at most k classification errors, where k is a given integer. We present a… (More)
DOI: 10.1016/j.ipl.2017.06.011


Figures and Tables

Sorry, we couldn't extract any figures or tables for this paper.

Slides referencing similar topics