demo/diabetes.r

In catnet: Categorical Bayesian Network Inference

source("diabetesLoad.r")
source("cvKfold.r")

npars <- 1
ncats <- 3
pathwayFile <- "c2.cp.kegg.v3.0.symbols.gmt"

avrres <- NULL
cvmean <- NULL
cvstderr <- NULL
cvpathway <- NULL
for(nn in (1+length(avrres)):186) {
  d <- load.gsea(pathwayFile,nn,npars,ncats)
  if(nrow(d$cdata)*ncol(d$cdata) <= 0 || nrow(d$cdata) <= 1)
    next
  ddata <- cnDiscretize(d$cdata, ncats, "uniform")
  res10 <- NULL
  for(k in 1:10)
    res10 <- rbind(res10, classification.cv10fold(d$cdata,d$cls,d$pathway,ddata,npars,d$nodePars,ncats,d$nodeCats,d$nodeOrder,ker="radial",0.03, folds=10,echo=FALSE))
  sc <- max(mean(unlist(res10[,1])), mean(unlist(res10[,2])), mean(unlist(res10[,3])), mean(unlist(res10[,4])), mean(unlist(res10[,5])), mean(unlist(res10[,6])), mean(unlist(res10[,7])))
  if(sc > 60) {
    for(k in 1:10)
      res10 <- rbind(res10, classification.cv10fold(d$cdata,d$cls,d$pathway,ddata,npars,d$nodePars,ncats,d$nodeCats,d$nodeOrder,ker="radial",0.03, folds=10,echo=FALSE))
    err <- try(postscript(paste("./kegg/diabetes_", d$pathname, "_p1c3.ps", sep="")), silent=TRUE)
    if(is.null(err)) {
      boxplot(list(NB=unlist(res10[,1]), BN.0=unlist(res10[,2]), BN.BIC=unlist(res10[,3]), BN.AIC=unlist(res10[,4]), SVM=unlist(res10[,5]), LASSO=unlist(res10[,6]), LAR=unlist(res10[,7])), main=paste("Diabetes, ", d$pathname, sep=""))
      dev.off()
    }
  }
  cvmean <- rbind(cvmean, c(mean(unlist(res10[,1])), mean(unlist(res10[,2])), mean(unlist(res10[,3])), mean(unlist(res10[,4])), mean(unlist(res10[,5])), mean(unlist(res10[,6])), mean(unlist(res10[,7]))))
  cvstderr <- rbind(cvstderr, c(sqrt(var(unlist(res10[,1]))), sqrt(var(unlist(res10[,2]))), sqrt(var(unlist(res10[,3]))), sqrt(var(unlist(res10[,4]))), sqrt(var(unlist(res10[,5]))), sqrt(var(unlist(res10[,6]))), sqrt(var(unlist(res10[,7])))))
  sc <- max(mean(unlist(res10[,1])), mean(unlist(res10[,2])), mean(unlist(res10[,3])), mean(unlist(res10[,4])), mean(unlist(res10[,5])), mean(unlist(res10[,6])), mean(unlist(res10[,7])))
  avrres <- c(avrres, sc)
  cvpathway <- c(cvpathway, d$pathname)
  cat(nn,": ", sc,"\n")
}

tt <- cbind(cvpathway,cvmean,cvstderr, avrres)
colnames(tt) <- c("pathway", "NB", "BN.0", "BN.BIC", "BN.AIC", "SVM", "LASSO", "LAR", "STD.NB", "STD.BN.0", "STD.BN.BIC", "BN.NET.AIC", "STD.SVM", "STD.LASSO", "STD.LAR", "maxscore")
write.csv(tt, "diabetes_cv10_p1c3.csv")