Ueda, N.; Saito, K. (2002). Parametric mixture models for multi-labeled text. In Advances in neural information processing systems, 721--728.
yahoo_health
mldr.datasets::get.mldr("yahoo_health")
Summary
| Instances | 9205 |
|---|---|
| Attributes | 30637 |
| Inputs | 30605 |
| Labels | 32 |
| Labelsets | 335 |
| Single labelsets | 169 |
| Max frequency | 2832 |
| Cardinality | 1.6441 |
| Density | 0.0514 |
| Mean IR | 653.5306 |
| SCUMBLE | 0.092 |
| TCS | 19.6088 |
Citation
Ueda, N.; Saito, K. (2002). Parametric mixture models for multi-labeled text. In Advances in neural information processing systems, 721--728.
@inproceedings{,
title="Parametric mixture models for multi-labeled text",
author="Ueda, N. and Saito, K.",
booktitle="Advances in neural information processing systems",
pages="721--728",
year="2002"
}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.