AC | R Documentation |
This function creates the centers of data nuggets from a random sample.
AC(x,
R,
delete.percent,
DN.num1,
DN.num2)
x |
A data matrix (of class matrix, data.frame, or data.table) containing only entries of class numeric. |
R |
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]. |
delete.percent |
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). |
DN.num1 |
The number of initial data nugget centers to create. Must be of class numeric. |
DN.num2 |
The number of data nuggets to create. Must be of class numeric. |
This function is used for calculating the arithmetic complexicity of the algorithm behind the create.DN function for the given parameter choices.
my.AC |
The arithmetic complexicity of the algorithm behind the create.DN function for the given parameter choices on a log10 scale. |
Traymon Beavers, Javier Cabrera, Mariusz Lubomirski
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.
Beavers, T., Cheng, G., Duan, Y., Cabrera, J., Lubomirski, M., Amaratunga, D., Teigler, J. (2023). Data Nuggets: A Method for Reducing Big Data While Preserving Data Structure (Submitted for Publication)
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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