VirusGO 

mldr.datasets::get.mldr("VirusGO")

Select your download

Full dataset

MULAN/MEKA (.arff) MULAN (.xml) LibSVM KEEL mldr

Partitions: select your desired partitioning strategy, validation and format

Random Stratified Iterative stratified
Hold out MULAN MEKA LibSVM KEEL mldr MULAN MEKA LibSVM KEEL mldr MULAN MEKA LibSVM KEEL mldr
2x5-fold cross validation MULAN MEKA LibSVM KEEL mldr MULAN MEKA LibSVM KEEL mldr MULAN MEKA LibSVM KEEL mldr
10-fold cross validation MULAN MEKA LibSVM KEEL mldr MULAN MEKA LibSVM KEEL mldr MULAN MEKA LibSVM KEEL mldr

Summary

Instances 207
Attributes 755
Inputs 749
Labels 6
Labelsets 17
Single labelsets 6
Max frequency 56
Cardinality 1.2174
Density 0.2029
Mean IR 4.0412
SCUMBLE 0.0079
TCS 11.2437

Citation

Text

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.

BibTeX

@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.

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