birds

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

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 645
Attributes 279
Inputs 260
Labels 19
Labelsets 133
Single labelsets 73
Max frequency 294
Cardinality 1.014
Density 0.0534
Mean IR 5.407
SCUMBLE 0.033
TCS 13.3955

Citation

Briggs, F.; Lakshminarayanan, B.; Neal, L.; Fern, X. Z.; Raich, R.; Hadley, S. J. K.; Hadley, A. S.; Betts, M. G. (2012). Acoustic classification of multiple simultaneous bird species: A multi-instance multi-label approach. In The Journal of the Acoustical Society of America, 131(6), 4640--4650.
@article{,
  title="Acoustic classification of multiple simultaneous bird species: A multi-instance multi-label approach",
  author="Briggs, F. and Lakshminarayanan, B. and Neal, L. and Fern, X. Z. and Raich, R. and Hadley, S. J. K. and Hadley, A. S. and Betts, M. G.",
  journal="The Journal of the Acoustical Society of America",
  volume="131",
  number="6",
  pages="4640--4650",
  year="2012"
}

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.