foodtruck: Foodtruck multi-label dataset.
In rivolli/utiml: Utilities for Multi-Label Learning
Description
Usage
Format
Details
Source
Description
The foodtruck multi-label dataset is a real multi-label dataset, which uses
habits and personal information to predict food truck cuisines.
Usage
1
Format
A mldr object with 407 instances, 21 features and 12 labels:
Details
General Information
Cardinality: 2.28
Density: 0.19
Distinct multi-labels: 117
Number of single labelsets: 74
Max frequency: 114
Source
The dataset is described in:
Rivolli A., Parker L.C., de Carvalho A.C.P.L.F. (2017) Food Truck
Recommendation Using Multi-label Classification. In: Oliveira E., Gama J.,
Vale Z., Lopes Cardoso H. (eds) Progress in Artificial Intelligence. EPIA
2017. Lecture Notes in Computer Science, vol 10423. Springer, Cham
rivolli/utiml documentation built on June 1, 2021, 11:48 p.m.
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Description Usage Format Details Source
Description
The foodtruck multi-label dataset is a real multi-label dataset, which uses habits and personal information to predict food truck cuisines.
Usage
1 |
Format
A mldr object with 407 instances, 21 features and 12 labels:
Details
General Information
Cardinality: 2.28
Density: 0.19
Distinct multi-labels: 117
Number of single labelsets: 74
Max frequency: 114
Source
The dataset is described in: Rivolli A., Parker L.C., de Carvalho A.C.P.L.F. (2017) Food Truck Recommendation Using Multi-label Classification. In: Oliveira E., Gama J., Vale Z., Lopes Cardoso H. (eds) Progress in Artificial Intelligence. EPIA 2017. Lecture Notes in Computer Science, vol 10423. Springer, Cham
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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