spd_lesh {gdverse} | R Documentation |
shap power of determinants
Description
Function for calculate shap power of determinants SPD
.
Usage
spd_lesh(formula, data, cores = 1, ...)
Arguments
formula |
A formula of calculate shap power of determinants. |
data |
A data.frame or tibble of observation data. |
cores |
(optional) Positive integer (default is 1). When cores are greater than 1, use multi-core parallel computing. |
... |
(optional) Other arguments passed to |
Details
The power of shap power of determinants formula is
\theta_{x_j} \left( S \right) = \sum\limits_{s \in M \setminus \{x_j\}} \frac{|S|! \left(|M| - |S| - 1\right)!}{|M|!}\left(v \left(S \cup \left\{x_j\right\} \right) - v\left(S\right)\right)
.
shap power of determinants (SPD) is the contribution of variable x_j
to the power of determinants.
Value
A tibble with variable and its corresponding SPD
value.
Note
The shap power of determinants (SPD) requires at least 2^n-1
calculations when has n
explanatory variables.
When there are more than 10 explanatory variables, carefully consider the computational burden of this model.
When there are a large number of explanatory variables, the data dimensionality reduction method can be used
to ensure the trade-off between analysis results and calculation speed.
Author(s)
Wenbo Lv lyu.geosocial@gmail.com
References
Li, Y., Luo, P., Song, Y., Zhang, L., Qu, Y., & Hou, Z. (2023). A locally explained heterogeneity model for examining wetland disparity. International Journal of Digital Earth, 16(2), 4533–4552. https://doi.org/10.1080/17538947.2023.2271883
Examples
data('ndvi')
g = spd_lesh(NDVIchange ~ ., data = ndvi)
g