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Documentation Index

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shademts combines SHADE with MTS-LS1 (Multiple Trajectory Search Local Search 1), a coordinate-wise local search that perturbs individual dimensions. MTS-LS1 is applied to the best individual every ls_freq generations.

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Usage

shademts(
  NP = 40,
  G = 100,
  data,
  class.name,
  c = 0.1,
  structure = c("nb", "tancl", "tan", "hc"),
  pB = 0.05,
  edgelist = NULL,
  ls_freq = 3,
  ls_max_dims = 200,
  verbose = 25,
  ...
)

​
Parameters

​
NP
integer
default:"40"
Population size.
​
G
integer
default:"100"
Maximum generations.
​
data
data.frame
required
Training data frame.
​
class.name
character
required
Class variable column name.
​
c
numeric
default:"0.1"
SHADE adaptation rate. Range [0, 0.2].
​
structure
character
default:"nb"
BN structure: "nb", "tan", "tancl", "hc".
​
pB
numeric
default:"0.05"
Fraction of best individuals for mutation.
​
edgelist
matrix
Optional custom BN topology (edges × 2 matrix).
​
ls_freq
integer
default:"3"
Apply MTS-LS1 every this many generations.
​
ls_max_dims
integer
default:"200"
Maximum number of dimensions to perturb per local search call.
​
verbose
integer
default:"25"
Print progress every this many generations.
​
...
Extra arguments for bnclassify::tan_cl or bnclassify::tan_hc.

​
Return value

Object of class DE: Best, BestCLL, pobFinal, CLLPobFinal, N.evals, convergence, evaluations.

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Example

library(dplbnDE)
data(car)

result <- shademts(
  NP = 20, G = 25,
  data = car,
  class.name = names(car)[7],
  structure = "tan",
  ls_freq = 3,
  verbose = 5
)
print(result)