SRCL_5_layerwise_relevance_propagation: Layer-wise relevance propagation of the fitted monotonistic...
In ekstroem/SRCL: Synergistic Risk Contributions Learning
Description
Usage
Arguments
Examples
View source: R/SRCL_functions.R
Description
Calculates risk contributions for each exposure and a baseline using layer-wise relevance propagation of the fitted monotonistic neural network and data.
Usage
1
SRCL_5_layerwise_relevance_propagation(X, model)
Arguments
X
The exposure data
model
The fitted the monotonistic neural network
Examples
1
#See the example under SRCL_0_synthetic_data
ekstroem/SRCL documentation built on Sept. 5, 2020, 8:59 p.m.
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Description Usage Arguments Examples
View source: R/SRCL_functions.R
Description
Calculates risk contributions for each exposure and a baseline using layer-wise relevance propagation of the fitted monotonistic neural network and data.
Usage
1 | SRCL_5_layerwise_relevance_propagation(X, model)
|
Arguments
X |
The exposure data |
model |
The fitted the monotonistic neural network |
Examples
1 | #See the example under SRCL_0_synthetic_data
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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