A Machine Learning Framework for Balancing Training Sets of Sensor Sequential Data Streams

The recent explosive growth in the number of smart technologies relying on data collected from sensors and processed with machine learning classifiers made the training data imbalance problem more visible than ever before. Class-imbalanced sets used to train models of various events of interest are...

Descripción completa

Detalles Bibliográficos
Autores principales: Setiawan, Budi Darma, Serdült, Uwe, Kryssanov, Victor
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8540530/
https://www.ncbi.nlm.nih.gov/pubmed/34696105
http://dx.doi.org/10.3390/s21206892

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8540530/
https://www.ncbi.nlm.nih.gov/pubmed/34696105
http://dx.doi.org/10.3390/s21206892

Ejemplares similares