Improving outliers detection in data streams using LiCS and voting
Detecting outliers in real-time is increasingly important for many real-world applications such as detecting abnormal heart activity, intrusions to systems, spams or abnormal credit card transactions. However, detecting outliers in data streams rises many challenges such as high-dimensionality, dyna...
Guardado en:
Autores principales: | Fatima-Zahra Benjelloun, Ahmed Oussous, Amine Bennani, Samir Belfkih, Ayoub Ait Lahcen |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Elsevier
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/27690865aa2042bcb85cf54db30f0f6b |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Outliers detection and treatment: a review.
por: Denis Cousineau, et al.
Publicado: (2010) -
Anomaly Detection on Data Streams for Smart Agriculture
por: Juliet Chebet Moso, et al.
Publicado: (2021) -
Data Stream Mining Between Classical and Modern Applications: A Review
por: Ammar Thaher Yaseen Al Abd Alazeez Al Abd Alazeez
Publicado: (2021) -
Demand-Driven Data Acquisition for Large Scale Fleets
por: Philip Matesanz, et al.
Publicado: (2021) -
A hybrid machine learning method for increasing the performance of network intrusion detection systems
por: Achmad Akbar Megantara, et al.
Publicado: (2021)