Cargando…
A survival analysis based volatility and sparsity modeling network for student dropout prediction
Student Dropout Prediction (SDP) is pivotal in mitigating withdrawals in Massive Open Online Courses. Previous studies generally modeled the SDP problem as a binary classification task, providing a single prediction outcome. Accordingly, some attempts introduce survival analysis methods to achieve c...
Autores principales: | Pan, Feng, Huang, Bingyao, Zhang, Chunhong, Zhu, Xinning, Wu, Zhenyu, Zhang, Moyu, Ji, Yang, Ma, Zhanfei, Li, Zhengchen |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9071151/ https://www.ncbi.nlm.nih.gov/pubmed/35512010 http://dx.doi.org/10.1371/journal.pone.0267138 |
Ejemplares similares
-
Student Dropout Prediction
por: Del Bonifro, Francesca, et al.
Publicado: (2020) -
Explorability and the origin of network sparsity in living systems
por: Busiello, Daniel M., et al.
Publicado: (2017) -
Groupwise structural sparsity for discriminative voxels identification
por: Ji, Hong, et al.
Publicado: (2023) -
Sparsity-Based Spatial Interpolation in Wireless Sensor Networks
por: Guo, Di, et al.
Publicado: (2011) -
Backpropagation With Sparsity Regularization for Spiking Neural Network Learning
por: Yan, Yulong, et al.
Publicado: (2022)