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diff --git a/LICENSE.html b/LICENSE.html index f1a1d4c..d56a974 100644 --- a/LICENSE.html +++ b/LICENSE.html @@ -25,7 +25,7 @@ diff --git a/articles/basic_use.html b/articles/basic_use.html index 205290d..5b50d50 100644 --- a/articles/basic_use.html +++ b/articles/basic_use.html @@ -43,7 +43,7 @@ diff --git a/articles/geographic.html b/articles/geographic.html index 42061cc..cdf2c4e 100644 --- a/articles/geographic.html +++ b/articles/geographic.html @@ -43,7 +43,7 @@ diff --git a/articles/index.html b/articles/index.html index 8a70e2c..83575d1 100644 --- a/articles/index.html +++ b/articles/index.html @@ -25,7 +25,7 @@ diff --git a/articles/multiple_output.html b/articles/multiple_output.html index 27042d4..33ec6fc 100644 --- a/articles/multiple_output.html +++ b/articles/multiple_output.html @@ -43,7 +43,7 @@ diff --git a/articles/tidymodels.html b/articles/tidymodels.html index 738d455..0e792d6 100644 --- a/articles/tidymodels.html +++ b/articles/tidymodels.html @@ -43,7 +43,7 @@ diff --git a/authors.html b/authors.html index d3aa090..2575496 100644 --- a/authors.html +++ b/authors.html @@ -25,7 +25,7 @@ @@ -94,13 +94,13 @@Mayer M (2024). shapviz: SHAP Visualizations. -R package version 0.9.6, https://modeloriented.github.io/shapviz/, https://github.com/ModelOriented/shapviz. +R package version 0.9.7, https://modeloriented.github.io/shapviz/, https://github.com/ModelOriented/shapviz.
@Manual{, title = {shapviz: SHAP Visualizations}, author = {Michael Mayer}, year = {2024}, - note = {R package version 0.9.6, https://modeloriented.github.io/shapviz/}, + note = {R package version 0.9.7, https://modeloriented.github.io/shapviz/}, url = {https://github.com/ModelOriented/shapviz}, }diff --git a/index.html b/index.html index 24c4e17..457b1c6 100644 --- a/index.html +++ b/index.html @@ -45,7 +45,7 @@ @@ -122,7 +122,7 @@
SHAP and feature values are stored in a “shapviz” object that is built from:
NEWS.md
+ This function creates an object of class "shapviz" from a matrix of SHAP values, or from a fitted model of type
XGBoost,
LightGBM, or
H2O (tree-based regression or binary classification model).
H2O (tree-based models).
Furthermore, shapviz()
can digest the results of
shapr::explain()
,
treeshap::treeshap()
,