Xu, Jianhua; Liu, Jiali; Yin, Jing; Sun, Chengyu (2016). A multi-label feature extraction algorithm via maximizing feature variance and feature-label dependence simultaneously. In Knowledge-Based Systems, 98(), 172--184.
GnegativeGO
mldr.datasets::get.mldr("GnegativeGO")
Summary
Instances | 1392 |
---|---|
Attributes | 1725 |
Inputs | 1717 |
Labels | 8 |
Labelsets | 19 |
Single labelsets | 5 |
Max frequency | 533 |
Cardinality | 1.046 |
Density | 0.1307 |
Mean IR | 18.4476 |
SCUMBLE | 0.0096 |
TCS | 12.4722 |
Citation
Xu, Jianhua; Liu, Jiali; Yin, Jing; Sun, Chengyu (2016). A multi-label feature extraction algorithm via maximizing feature variance and feature-label dependence simultaneously. In Knowledge-Based Systems, 98(), 172--184.
@article{,
title={A multi-label feature extraction algorithm via maximizing feature variance and feature-label dependence simultaneously},
author={Xu, Jianhua and Liu, Jiali and Yin, Jing and Sun, Chengyu},
journal={Knowledge-Based Systems},
volume={98},
pages={172--184},
year={2016},
publisher={Elsevier}
}
Concurrence plot
In this concurrence plot, sectors represent labels and links between them depict label co-occurrences. SCUMBLE is a measure designed to assess the concurrence among imbalanced labels.