fitnessEvolution | R Documentation |
Get the fitness of the best / average chromosomes after each generation
fitnessEvolution(
object,
what = c("mean", "best", "std.dev"),
type = c("true", "raw")
)
object |
The |
what |
can be one ore more of |
type |
one of |
Returns the progress of the fitness of the best or average chromosome.
A vector with the best or average fitness value after each generation
ctrl <- genAlgControl(populationSize = 100, numGenerations = 15, minVariables = 5,
maxVariables = 12, verbosity = 1)
evaluator <- evaluatorPLS(numReplications = 2, innerSegments = 7, testSetSize = 0.4,
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)
fitness(result) # Get fitness of the found subsets
h <- fitnessEvolution(result) # Get average fitness as well as the fitness of the
# best chromosome for each generation (at raw scale!)
plot(h[, "mean"], type = "l", col = 1, ylim = c(-7, -1))
lines(h[, "mean"] - h[, "std.dev"], type = "l", col = "gray30", lty = 2)
lines(h[, "mean"] + h[, "std.dev"], type = "l", col = "gray30", lty = 2)
lines(h[, "best"], type = "l", col = 2)
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