foodtruck: Foodtruck multi-label dataset.
In 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
utiml documentation built on May 31, 2021, 9:09 a.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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