simulatedRankingData: Simulated ranking data
In adabag: Applies Multiclass AdaBoost.M1, SAMME and Bagging
simulatedRankingData R Documentation
Simulated ranking data
Description
The simulatedRankingData dataset is a list that includes the following components:
The ranking matrix, y, contains the ranking matrix. It consists of 500 rows and 4 columns, indicating the ranking positions. Each element in the matrix represents the rank assigned to an individual for a particular item.
The predictor matrix x in the dataset consists of 20 continuous explanatory variables. These variables are used for predicting the rankings.
Usage
data(simulatedRankingData)
References
Albano, A., Sciandra, M., and Plaia, A. (2023): "A weighted distance-based approach with boosted decision trees for label ranking." Expert Systems with Applications.
adabag documentation built on May 31, 2023, 9:09 p.m.
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| simulatedRankingData | R Documentation |
Simulated ranking data
Description
The simulatedRankingData dataset is a list that includes the following components:
The ranking matrix, y, contains the ranking matrix. It consists of 500 rows and 4 columns, indicating the ranking positions. Each element in the matrix represents the rank assigned to an individual for a particular item.
The predictor matrix x in the dataset consists of 20 continuous explanatory variables. These variables are used for predicting the rankings.
Usage
data(simulatedRankingData)References
Albano, A., Sciandra, M., and Plaia, A. (2023): "A weighted distance-based approach with boosted decision trees for label ranking." Expert Systems with Applications.
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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