getAUC

This function calls <code>[kohonen]{xgboost}</code> to train the classifier, followed by calculating the similarity between the two given datasets. The return value is a AUC index, ranging between 0 and 1, where the AUC is closer to 0.5, the more similar the two data sets is.

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

getAUC function

<dl><dt>data1</dt>
<dd>Dataset 1, the data type must be numeric, matrix or Data.frame.</dd>
<dt>data2</dt>
<dd>Dataset 2, the data type must be numeric, matrix or Data.frame.</dd></dl>

Arguments

Get the AUC value between two datasets — getAUC

<dl>

<dt>data1</dt>
<dd>Dataset 1, the data type must be numeric, matrix or Data.frame.</dd>


<dt>data2</dt>
<dd>Dataset 2, the data type must be numeric, matrix or Data.frame.</dd>

</dl>

getAUC: Get the AUC value between two datasets

Description

Usage

Value

Arguments