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This function creates the centers of data nuggets from a random sample.
AC(x,
R,
delete.percent,
DN.num1,
DN.num2)
The arithmetic complexicity of the algorithm behind the create.DN function for the given parameter choices on a log10 scale.
A data matrix (of class matrix, data.frame, or data.table) containing only entries of class numeric.
The number of observations to sample from the data matrix when creating the initial data nugget centers. Must be of class numeric within [100,10000].
The proportion of observations to remove from the data matrix at each iteration when finding data nugget centers. Must be of class numeric and within (0,1).
The number of initial data nugget centers to create. Must be of class numeric.
The number of data nuggets to create. Must be of class numeric.
Traymon Beavers, Javier Cabrera, Mariusz Lubomirski
This function is used for calculating the arithmetic complexicity of the algorithm behind the create.DN function for the given parameter choices.
Beavers, T. E., Cheng, G., Duan, Y., Cabrera, J., Lubomirski, M., Amaratunga, D., & Teigler, J. E. (2024). Data Nuggets: A Method for Reducing Big Data While Preserving Data Structure. Journal of Computational and Graphical Statistics, 1-21.
Cherasia, K. E., Cabrera, J., Fernholz, L. T., & Fernholz, R. (2022). Data Nuggets in Supervised Learning. In Robust and Multivariate Statistical Methods: Festschrift in Honor of David E. Tyler (pp. 429-449). Cham: Springer International Publishing.
X = cbind.data.frame(rnorm(10^6),
rnorm(10^6),
rnorm(10^6),
rnorm(10^6),
rnorm(10^6))
my.AC = AC(x = X,
R = 5000,
delete.percent = .1,
DN.num1 = 10^4,
DN.num2 = 2000)
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