Scalable Multilabel Learning Based on Feature and Label Dimensionality Reduction
The data-driven management of real-life systems based on a trained model, which in turn is based on the data gathered from its daily usage, has attracted a lot of attention because it realizes scalable control for large-scale and complex systems. To obtain a model within an acceptable computational...
Saved in:
Main Authors: | Jaesung Lee, Dae-Won Kim |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2018-01-01
|
Series: | Complexity |
Online Access: | http://dx.doi.org/10.1155/2018/6292143 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Leveraging Partial Labels for Cervical Lesion Classification via a Multilabel Approach
by: Margaret Dy Manalo, et al.
Published: (2025-01-01) -
A Variable Precision Attribute Reduction Approach in Multilabel Decision Tables
by: Hua Li, et al.
Published: (2014-01-01) -
Multilabel Image Annotation Based on Double-Layer PLSA Model
by: Jing Zhang, et al.
Published: (2014-01-01) -
Real-Time On-Device Continual Learning Based on a Combined Nearest Class Mean and Replay Method for Smartphone Gesture Recognition
by: Heon-Sung Park, et al.
Published: (2025-01-01) -
Many Local Pattern Texture Features: Which Is Better for Image-Based Multilabel Human Protein Subcellular Localization Classification?
by: Fan Yang, et al.
Published: (2014-01-01)