how to remove features with near zero variance, not useful for discriminating classes

knnRemoveZeroVarCols_kaggleDigitRecognizer

# helpful functions for classification/regression training
# http://cran.r-project.org/web/packages/caret/index.html
library(caret)

# get indices of data.frame columns (pixels) with low variance
badCols <- nearZeroVar(train)
print(paste("Fraction of nearZeroVar columns:", round(length(badCols)/length(train),4)))

# remove those "bad" columns from the training and cross-validation sets
train <- train[, -badCols]
cv <- cv[, -badCols]