search for: big_data_set

...UT 600 Mb MEMORY. # # I WOULD BE HAPPY ABOUT ANY HINT HOW TO IMPROVE THIS. # Pre-filter the big data set (more than 115,000 rows and 524 columns) for later class predictions. # The big data set contains the same column names as the training set, but in a different order. input.file <- 'big_data_set.txt' filtered.file <- 'big_data_set_filtered.txt' # Read header with first row prediction.set <- read.csv(input.file, header=TRUE, skip=0, nrow=1) # Prepare column names by stripping the underline and the number at the end colnames(prediction.set) <- sub('_\\d+$', &...