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.
GpositivePseAAC
mldr.datasets::get.mldr("GpositivePseAAC")
Summary
Instances | 519 |
---|---|
Attributes | 444 |
Inputs | 440 |
Labels | 4 |
Labelsets | 7 |
Single labelsets | 2 |
Max frequency | 206 |
Cardinality | 1.0077 |
Density | 0.2519 |
Mean IR | 3.8605 |
SCUMBLE | 0.001 |
TCS | 9.419 |
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.