EvaluationFunction {dGAselID}

EvaluationFunction

Description

Evaluates the individuals' fitnesses.

Usage

EvaluationFunction(x, individuals, response, method, trainTest, nnetSize = NA,
  nnetDecay = NA, rdaAlpha = NA, rdaDelta = NA, ...)

Arguments

x

Dataset in ExpressionSet format.

individuals

Population of individuals with diploid genotypes.

response

Response variable.

method

Supervised classifier for fitness evaluation. Most of the supervised classifiers in MLInterfaces are acceptable. The default is knn.cvI(k=3, l=2).

trainTest

Cross-validation method. The default is "LOG".

nnetSize

for nnetI. The default value is NA.

nnetDecay

for nnetI. The default value is NA.

rdaAlpha

for rdaI. The default value is NA.

rdaDelta

for rdaI. The default value is NA.

...

Additional arguments.

Examples

## Not run: 
 library(genefilter)
 library(ALL)
 data(ALL)
 bALL = ALL[, substr(ALL$BT,1,1) == "B"]
 smallALL = bALL[, bALL$mol.biol %in% c("BCR/ABL", "NEG")]
 smallALL$mol.biol = factor(smallALL$mol.biol)
 smallALL$BT = factor(smallALL$BT)
 f1 <- pOverA(0.25, log2(100))
 f2 <- function(x) (IQR(x) > 0.5)
 f3 <- ttest(smallALL$mol.biol, p=0.1)
 ff <- filterfun(f1, f2, f3)
 selectedsmallALL <- genefilter(exprs(smallALL), ff)
 smallALL = smallALL[selectedsmallALL, ]
 rm(f1)
 rm(f2)
 rm(f3)
 rm(ff)
 rm(bALL)
 sum(selectedsmallALL)
 set.seed(1357)

 population0<-InitialPopulation(smallALL, 14, 8, FALSE)
 individuals0<-Individuals(population0)
 results<-EvaluationFunction(smallALL, individuals0, response="mol.biol",
             method=knn.cvI(k=3, l=2), trainTest="LOG")
 
## End(Not run)