nlshadersp

NL-SHADE-RSP — Non-Linear population reduction SHADE with Ranked-based Selective Pressure

nlshadersp implements NL-SHADE-RSP: SHADE with exponential (non-linear) population size reduction and a ranked-based selective pressure mechanism that biases donor vector selection toward better-ranked individuals.

Usage

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

Parameters

NP · integer · default: "40"

Initial population size. Reduced non-linearly (exponentially) down to 4.

G · integer · default: "100"

Maximum generations.

data · data.frame · required

Data frame containing features and the class variable.

class.name · character · required

Name of the class variable column.

c · numeric · default: "0.1"

Adaptation rate for history memory. Must be in [0, 0.2].

structure · character · default: "nb"

BN structure: "nb", "tan", "tancl", or "hc".

pB · numeric · default: "0.05"

Fraction of best individuals for mutation strategy.

edgelist · matrix

Optional custom BN topology (edges × 2 matrix: from, to).

verbose · integer · default: "25"

Print progress every this many generations.

...

Extra arguments forwarded to bnclassify::tan_cl or bnclassify::tan_hc.

Return value

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

Example

library(dplbnDE)
data(car)

result <- nlshadersp(
  NP = 20, G = 25,
  data = car,
  class.name = names(car)[7],
  c = 0.1, pB = 0.05,
  structure = "tan",
  verbose = 5
)
print(result)