GenAlgLMEvaluator-constructor: LM Evaluator

In gaselect: Genetic Algorithm (GA) for Variable Selection from High-Dimensional Data

LM Evaluator

Description

Create an evaluator that uses a linear model to evaluate the fitness.

Usage

evaluatorLM(
  statistic = c("BIC", "AIC", "adjusted.r.squared", "r.squared"),
  numThreads = NULL
)

Arguments

statistic	The statistic used to evaluate the fitness
numThreads	The maximum number of threads the algorithm is allowed to spawn (a value less than 1 or NULL means no threads)

Details

Different statistics to evaluate the fitness of the variable subset can be given. If a maximum absolute correlation is given the algorithm will be very slow (as the C++ implementation can not be used anymore) and multithreading is not available.

Value

Returns an S4 object of type GenAlgLMEvaluator

See Also

Other GenAlg Evaluators: evaluatorFit(), evaluatorPLS(), evaluatorUserFunction()

Examples

ctrl <- genAlgControl(populationSize = 200, numGenerations = 30, minVariables = 5,
    maxVariables = 12, verbosity = 1)
evaluator <- evaluatorLM(statistic = "BIC", numThreads = 1)

# Generate demo-data
set.seed(12345)
X <- matrix(rnorm(10000, sd = 1:5), ncol = 50, byrow = TRUE)
y <- drop(-1.2 + rowSums(X[, seq(1, 43, length = 8)]) + rnorm(nrow(X), 1.5));

result <- genAlg(y, X, control = ctrl, evaluator = evaluator, seed = 123)

subsets(result, 1:5)

gaselect documentation built on June 22, 2024, 11:05 a.m.