Skip to content

Instantly share code, notes, and snippets.

@multidis

multidis/split_strat_scale.r

Created December 23, 2013 08:17
Show Gist options

  • Select an option

    Learn more about clone URLs
  • Save multidis/8093372 to your computer and use it in GitHub Desktop.

Select an option

Learn more about clone URLs
Save multidis/8093372 to your computer and use it in GitHub Desktop.
Download ZIP

Revisions

  1. multidis revised this gist Dec 27, 2013. 1 changed file with 8 additions and 1 deletion.
    9 changes: 8 additions & 1 deletion split_strat_scale.r
    View file
    Original file line number Diff line number Diff line change
    @@ -10,4 +10,11 @@ ytst <- yclass[-in.train]; summary(factor(ytst))
    Xtra <- scale(X[in.train,])
    Xtest <- scale(X[-in.train,],
    center = attr(Xtra,"scaled:center"),
    scale = attr(Xtra,"scaled:scale"))
    scale = attr(Xtra,"scaled:scale"))

    ## stratified folds for cross-validation: say Y is a factor
    table(Y)
    foldInds <- createFolds(Y, k=10, list=TRUE, returnTrain=FALSE)
    lapply(foldInds, function(ii) table(Y[ii])) ## verify stratification
    ## set returnTrain=TRUE if supplyinf these indiced to train-function,
    ## see https://stat.ethz.ch/pipermail/r-help/2011-May/277722.html
  2. multidis created this gist Dec 23, 2013.
    13 changes: 13 additions & 0 deletions split_strat_scale.r
    View file
    Original file line number Diff line number Diff line change
    @@ -0,0 +1,13 @@
    library(caret)

    ## select training indices preserving class distribution
    in.train <- createDataPartition(yclass, p=0.8, list=FALSE)
    summary(factor(yclass))
    ytra <- yclass[in.train]; summary(factor(ytra))
    ytst <- yclass[-in.train]; summary(factor(ytst))

    ## standardize features: training parameters of scaling for test-part
    Xtra <- scale(X[in.train,])
    Xtest <- scale(X[-in.train,],
    center = attr(Xtra,"scaled:center"),
    scale = attr(Xtra,"scaled:scale"))