setDataCols: Remove unwanted or keep interested columns from logit data

In novasmedley/gbmSpm: Find predictive sequential patterns for clinical glioblastoma patients

Description

Remove unwanted or keep interested columns from logit data

Usage

setDataCols(data, labelName, predictors = NULL, needToRemove = NULL)

Arguments

data	dataframe, rows are samples, cols are features plus some metadata not meant for modeling and will be removed
labelName	char, column name of binary label
predictors	char, names of columns in data that should be in logit fit data
needToRemove	char, names of columns in data that should not be in logit fit data

Value

data with removed columns, ready for logit modeling

Examples

data("features_ratechange_sup0.4g60l2z2") # features and labels for each clinical visit
t <- 'rate'
maxgap <- 60
maxlen <- 2

# format
names <- colnames(feats)
feats <- data.frame(id=row.names(feats),feats)
colnames(feats) <- c('id',names)
feats <- prepLaterality(feats)
feats <- prepLocation(feats)
feats <- removeVisits(feats,
                     maxgap=maxgap,
                     maxlength=maxlen,
                     tType=t,
                     save=F,
                     outDir=NA)
labels <- getClassLabels()
needToRemove <- c('id','iois','eventID', # remove ids
                  labels, # remove labels
                  'IDH1') # not interested

# data partitions
train.ids <- sample(feats$id, size=floor(0.80*nrow(feats)), replace = F) # random
feats <- feats[feats$id %in% train.ids,] #training data
ind <- getTrainingFolds(trainEvents=feats,
                        folds=3,
                        seed=1,
                        verbose=T)
feats <- setDataCols(data=feats, 
                    labelName='survivalIn60', 
                    needToRemove=needToRemove)
                    

novasmedley/gbmSpm documentation built on May 17, 2019, 10:39 a.m.