AC {datanugget} R Documentation

Calculate Arithmetic Complexicity of the Algorithm That Creates Data Nuggets

Description

This function creates the centers of data nuggets from a random sample.

Usage

AC(x,
R,
delete.percent,
DN.num1,
DN.num2)


Arguments

 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.

Details

This function is used for calculating the arithmetic complexicity of the algorithm behind the create.DN function for the given parameter choices.

Value

 my.AC The arithmetic complexicity of the algorithm behind the create.DN function for the given parameter choices on a log10 scale.

Author(s)

Traymon Beavers, Javier Cabrera, Mariusz Lubomirski

References

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)

Examples


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)



[Package datanugget version 1.2.4 Index]