Global Hierarchical Neural Networks using Hierarchical Softmax
2023-08-02Code Available0· sign in to hype
Jetze Schuurmans, Flavius Frasincar
Code Available — Be the first to reproduce this paper.
ReproduceCode
- github.com/jschuurmans/hsoftmaxOfficialIn paperpytorch★ 2
Abstract
This paper presents a framework in which hierarchical softmax is used to create a global hierarchical classifier. The approach is applicable for any classification task where there is a natural hierarchy among classes. We show empirical results on four text classification datasets. In all datasets the hierarchical softmax improved on the regular softmax used in a flat classifier in terms of macro-F1 and macro-recall. In three out of four datasets hierarchical softmax achieved a higher micro-accuracy and macro-precision.