Read, J.; Pfahringer, B.; Holmes, G.; Frank, E. (2011). Classifier chains for multi-label classification. In Machine Learning, 85(), 333--359.
imdb
mldr.datasets::get.mldr("imdb")
Summary
Instances | 120919 |
---|---|
Attributes | 1029 |
Inputs | 1001 |
Labels | 28 |
Labelsets | 4503 |
Single labelsets | 2263 |
Max frequency | 13144 |
Cardinality | 1.9997 |
Density | 0.0714 |
Mean IR | 25.124 |
SCUMBLE | 0.1082 |
TCS | 18.6535 |
Citation
Read, J.; Pfahringer, B.; Holmes, G.; Frank, E. (2011). Classifier chains for multi-label classification. In Machine Learning, 85(), 333--359.
@article{,
title = "Classifier chains for multi-label classification",
author = "Read, J. and Pfahringer, B. and Holmes, G. and Frank, E.",
journal = "Machine Learning",
year = "2011",
volume="85",
issue="3",
pages = "333--359"
}
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.