remainUnsample

Built-in function: This function is used in the semi-deterministic SS algorithm, and it contains two parameters X and Y, both of which are in an increased order. All data points in X vector that have not appeared in Y vector will be recorded and returned by this function.

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

remainUnsample function

<dl><dt>X</dt>
<dd>A vector that needs to be sampled.</dd>
<dt>Y</dt>
<dd>A vector with data samples from X.</dd></dl>

Arguments

Get the remain unsampled data after SSsample — remainUnsample

<dl>

<dt>X</dt>
<dd>A vector that needs to be sampled.</dd>


<dt>Y</dt>
<dd>A vector with data samples from X.</dd>

</dl>

remainUnsample: Get the remain unsampled data after `SSsample`

Description

Usage

Value

Arguments