Description
This function performs IM4E(Iterative Margin-Maximization under Max-Min Entropy) algorithm.
Usage
IM4E(
xx,
yy,
epsilon = 0.01,
sig = 1,
lambda = 1,
max_iter = 10,
removesmall = FALSE
)
Arguments
xx
model matrix of explanatory variables
epsilon
criterion for stopping iteration, default to be 0.01
sig
sigma used in algorithm, default to be 1
lambda
lambda used in algorithm, default to be 1
max_iter
maximum number of iteration
removesmall
whether remove features with small weights, default to be FALSE
Value
wweight vector obtained by IM4E algorithm
iter_numnumber of iteration for convergence
final_cfinal cost value. Refer to the cost function in reference below for more details
References
Bei Y, Hong P. Maximizing margin quality and quantity[C]//Machine Learning for Signal Processing (MLSP), 2015 IEEE 25th International Workshop on. IEEE, 2015: 1-6.
Examples
Run this code# NOT RUN {
data(park)
xx<-park$xx
yy<-park$yy
re<-IM4E(xx,yy)
print(re)
# }
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