BNhold: AID348 hold-out data using Burden Numbers for testing the EPX...
In EPX: Ensemble of Phalanxes
Description
Usage
Format
References
Description
AID348 hold-out data with 24 burden numbers as explanatory variables.
Demonstrates in a timely manner epx, the phalanx-formation
algorithm in EPX and associated functions summary.epx,
predict.epx , plot.epx, hit.curve.
Usage
1
Format
A dataframe with 3946 rows and 25 variables:
- WBN
Burden numbers descriptor set with 24 variables.
- y
The response variable where 1 denotes active and 0 inactive.
References
Tomal, J. H., Welch, W. J., & Zamar, R. H. (2015).
Ensembling classification models based on phalanxes of variables with
applications in drug discovery.
The Annals of Applied Statistics,
9(1), 69-93.
doi: 10.1214/14-AOAS778
EPX documentation built on July 7, 2021, 1:06 a.m.
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Description Usage Format References
Description
AID348 hold-out data with 24 burden numbers as explanatory variables.
Demonstrates in a timely manner epx, the phalanx-formation
algorithm in EPX and associated functions summary.epx,
predict.epx , plot.epx, hit.curve.
Usage
1 |
Format
A dataframe with 3946 rows and 25 variables:
- WBN
Burden numbers descriptor set with 24 variables.
- y
The response variable where 1 denotes active and 0 inactive.
References
Tomal, J. H., Welch, W. J., & Zamar, R. H. (2015). Ensembling classification models based on phalanxes of variables with applications in drug discovery. The Annals of Applied Statistics, 9(1), 69-93. doi: 10.1214/14-AOAS778
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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