splitdata: Split modeling data into test and train set
In StatMeasures: Easy Data Manipulation, Data Quality and Statistical Checks

Description Usage Arguments Details Value Author(s) See Also Examples

Takes in data, fraction (for train set) and seed, and returns train and test set

1	splitdata(data, fraction, seed = NULL)

`data`	a matrix, data.frame or data.table
`fraction`	proportion of observations that should go in the train set
`seed`	an integer value

An essential task before doing modeling is to split the modeling data into train and test sets. splitdata is built for this task and returns a list with train and test sets, which can be picked using the code given in example.

fraction corresponds to the train dataset, while the rest of the observations go to the test dataset. If the user wants to generate the same test and train dataset everytime, he should specify a seed value.

a list with two elements: train and test set

Akash Jain

actvspred, mape, accuracy, auc, iv, ks

# A 'data.frame'
df <- data.frame(x = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10),
                 y = c('a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j'),
                 z = c(1, 1, 0, 0, 1, 0, 0, 1, 1, 0))

# Split data into train (70%) and test (30%)
ltData <- splitdata(data = df, fraction = 0.7, seed = 123)
trainData <- ltData$train
testData <- ltData$test