SSsample

Built-in function: This function performs the SS algorithm.

Providing six different algorithms that can be used to split the
available data into training, test and validation subsets with similar distribution
for hydrological model developments. The dataSplit() function will help you divide
the data according to specific requirements, and you can refer to the par.default()
function to set the parameters for data splitting. The getAUC() function will help
you measure the similarity of distribution features between the data subsets.
For more information about the data splitting algorithms, please refer to:
Chen et al. (2022) <doi:10.1016/j.jhydrol.2022.128340>,
Zheng et al. (2022) <doi:10.1029/2021WR031818>.

Junyi Chen

DSAM

Data Splitting Algorithms for Model Developments

Feifei Zheng

SSsample function

<dl><dt>index</dt>
<dd>A subscript vector whose subscript corresponds to the output vector of the data point sorted in an ascending order.</dd>
<dt>prop</dt>
<dd>The sampling ratio, with the value ranging between 0 and 1.</dd></dl>

Arguments

Core function of SS sampling — SSsample

<dl>

<dt>index</dt>
<dd>A subscript vector whose subscript corresponds to the output vector of the data point sorted in an ascending order.</dd>


<dt>prop</dt>
<dd>The sampling ratio, with the value ranging between 0 and 1.</dd>

</dl>

SSsample: Core function of SS sampling

Description

Usage

Value

Arguments