Rivolli, Adriano; Parker, Larissa C; de Carvalho, Andre CPLF (2017). Food Truck Recommendation Using Multi-label Classification. In Portuguese Conference on Artificial Intelligence, 585--596.
foodtruck
mldr.datasets::get.mldr("foodtruck")
Summary
Instances | 407 |
---|---|
Attributes | 33 |
Inputs | 21 |
Labels | 12 |
Labelsets | 116 |
Single labelsets | 74 |
Max frequency | 115 |
Cardinality | 2.2899 |
Density | 0.1908 |
Mean IR | 7.0945 |
SCUMBLE | 0.1035 |
TCS | 10.283 |
Citation
Rivolli, Adriano; Parker, Larissa C; de Carvalho, Andre CPLF (2017). Food Truck Recommendation Using Multi-label Classification. In Portuguese Conference on Artificial Intelligence, 585--596.
@inproceedings{rivolli2017food,
title={Food Truck Recommendation Using Multi-label Classification},
author={Rivolli, Adriano and Parker, Larissa C and de Carvalho, Andre CPLF},
booktitle={Portuguese Conference on Artificial Intelligence},
pages={585--596},
year={2017},
organization={Springer},
doi={10.1007/978-3-319-65340-2\_48}
}
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.