Nested dichotomies are a standard statistical technique for tackling certain polytomous classification problems with logistic regression.

A system of nested dichotomies ( F o x , 1997 ) is a binary tree that recursively splits a set of classes from a multi- class classification problem into ...

In this paper we investigate two approaches to building balanced nested dichotomies—class-balanced nested dichotomies and data-balanced nested dichotomies—and ...

Ensembles of randomly- generated nested dichotomies have proven to be an effective approach to multi-class learning problems [1]. However, sampling trees by ...

In this paper, we investigate two approaches to building balanced nested dichotomies—class-balanced nested dichotomies and data-balanced nested dichotomies—and ...

Ensembles of nested dichotomies appear to be a good general-purpose method for applying binary classifiers to multi-class problems and are preferable if ...

In this paper we investigate two approaches to build- ing balanced nested dichotomies—class-balanced nested dichotomies and data-balanced nested dichotomies—and ...

Ensembles of randomly- generated nested dichotomies have proven to be an effective approach to multi-class learning problems [1]. However, sampling trees by ...

Two approaches to building balanced nested dichotomies are investigated and it is shown that both approaches can reduce runtime with little or no effect on ...

This study proposes novel ensemble class balanced nested dichotomy (EBND) fuzzy induction models for risk prediction in software requirement. Specifically ...