somCluster

Built-in function: This function performs clustering for a given dataset by calling the <code>[kohonen]{som}</code> function from a “kohonen” package.

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

somCluster function

<dl><dt>data</dt>
<dd>The dataset in matrix or data.frame, containing only input and output vectors, but with no subscript vector.</dd></dl>

Arguments

Self-organized map clustering — somCluster

<dl>

<dt>data</dt>
<dd>The dataset in matrix or data.frame, containing only input and output vectors, but with no subscript vector.</dd>

</dl>

somCluster: Self-organized map clustering

Description

Usage

Value

Arguments