A top-down supervised learning approach to hierarchical multi-label classification in networks

A top-down supervised learning approach to hierarchical multi-label classification in networks

Abstract Node classification is the task of inferring or predicting missing node attributes from information available for other nodes in a network. This paper presents a general prediction model to hierarchical multi-label classification, where the attributes to be inferred can be specified as a st...

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Bibliographic Details
Main Authors: Miguel Romero, Jorge Finke, Camilo Rocha
Format: Article
Language:English
Published: SpringerOpen 2022-02-01
Series:Applied Network Science
Subjects:
Hierarchical classification
Supervised learning
XGBoost
Top-down approach
Oryza sativa
Gene function prediction
Online Access:https://doi.org/10.1007/s41109-022-00445-3

Internet

https://doi.org/10.1007/s41109-022-00445-3

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