R: Data Splitting Algorithms for Model Developments

# Data Splitting Algorithms for Model Developments

## Documentation for package ‘DSAM’ version 1.0.2

- DESCRIPTION file.
- Package NEWS.

## Help Pages

checkFull | Check whether the sample set is full
dataSplit | Main function of data splitting algorithm
DP.initialSample | Initial sampling of DUPLEX
DP.reSample | Repeat sampling of DUPLEX
DSAM_test_largeData | large test dataset
DSAM_test_modData | Moderate test dataset
DSAM_test_smallData | Small test dataset
DUPLEX | 'DSAM' - DUPLEX algorithm
getAUC | Get the AUC value between two datasets
getMax | Get the maximum of the output column from the original data set
getMean | Get the mean and standard deviation of the output column from the original data set
getMin | Get the minimum of the output column from the original data set
getSnen | Get sampling number of each SOM neuron
MDUPLEX | 'DSAM' - MDUPLEX algorithm
par.default | Default parameter list
remainUnsample | Get the remain unsampled data after 'SSsample'
SBSS.P | 'DSAM' - SBSS.P algorithm
selectData | Select specific split data
somCluster | Self-organized map clustering
SOMPLEX | 'DSAM' - SOMPLEX algorithm
SS | 'DSAM' - SS algorithm
SSsample | Core function of SS sampling
standardise | Standardized data
TIMECON | 'DSAM' - Time-consecutive algorithm