ng20

mldr.datasets::get.mldr("ng20")

Select your download

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 19300
Attributes 1026
Inputs 1006
Labels 20
Labelsets 55
Single labelsets 17
Max frequency 997
Cardinality 1.0289
Density 0.0514
Mean IR 1.0073
SCUMBLE 1.3178e-07
TCS 13.9168

Citation

Ken Lang (1995). Newsweeder: Learning to filter netnews. In Proc. 12th International Conference on Machine Learning, 331--339.
@inproceedings{,
  author = "Ken Lang",
  title = "Newsweeder: Learning to filter netnews",
  booktitle = "Proc. 12th International Conference on Machine Learning",
  pages = "331--339",
  year = "1995"
}

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.