Ueda, N.; Saito, K. (2002). Parametric mixture models for multi-labeled text. In Advances in neural information processing systems, 721--728.
yahoo_computers
mldr.datasets::get.mldr("yahoo_computers")
Summary
| Instances | 12444 |
|---|---|
| Attributes | 34129 |
| Inputs | 34096 |
| Labels | 33 |
| Labelsets | 428 |
| Single labelsets | 239 |
| Max frequency | 4122 |
| Cardinality | 1.5072 |
| Density | 0.0457 |
| Mean IR | 176.6952 |
| SCUMBLE | 0.0965 |
| TCS | 19.9926 |
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.