Immigrate {Immigrate}

Immigrate

Description

This function performs IMMIGRATE(Iterative Max-Min Entropy Margin-Maximization with Interaction Terms ) algorithm. IMMIGRATE is a hypothesis-margin based feature selection method with interaction terms. Its weight matrix reflects the relative importance of features and their iteractions, which can be used for feature selection.

Usage

Immigrate(
  xx,
  yy,
  w0,
  epsilon = 0.01,
  sig = 1,
  max_iter = 10,
  removesmall = FALSE,
  randomw0 = FALSE
)

Arguments

xx

model matrix of explanatory variables

yy

label vector

w0

initial weight matrix, default to be diagonal matrix when missing

epsilon

criterion for stopping iteration

sig

sigma used in algorithm, default to be 1. Refer to the cost function in the link below for more details

max_iter

maximum number of iteration

removesmall

whether to remove features with small weights, default to be FALSE

randomw0

whether to use randomly initial weights, default to be FALSE

Value

w

weight matrix obtained by IMMIGRATE algorithm

iter_num

number of iteration for convergence

final_c

final cost value. Refer to the cost function in link below for more details

References

Zhao, Ruzhang, Pengyu Hong, and Jun S. Liu. "IMMIGRATE: A Margin-based Feature Selection Method with Interaction Terms." Entropy 22.3 (2020): 291.

See Also

Please refer to https://www.mdpi.com/1099-4300/22/3/291/htm for more details.

Please refer to https://github.com/RuzhangZhao/Immigrate/ for implementation demo.

Examples

data(park)
xx<-park$xx
yy<-park$yy
re<-Immigrate(xx,yy)
print(re)