Tag: R
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Interpret Complex Linear Models with SHAP within Seconds
Peaking into richly parametrized linear models with SHAP? Yes!
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Kernel SHAP in R and Python
“R Python” continued… Kernel SHAP
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Kernel SHAP
Standard Kernel SHAP has arrived in R. We show how well it plays together with deep learning in Keras
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shapviz goes H2O
The “shapviz” package now plays well together with H2O.
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Visualize SHAP Values without Tears
Visualize SHAP values without tears.
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Let the flashlight shine with plotly
How to combine model interpretation package “flashlight” with “plotly”?
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DuckDB: Quacking SQL
“R Python” continued… DuckDB: Quacking SQL
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Avoid loops in R! Really?
It must have been around the year 2000, when I wrote my first snipped of SPLUS/R code. One thing I’ve learned back then: Loops are slow. Replace them with vectorized calculations or if vectorization is not possible, use sapply() et al. Since then, the R core team and the community has invested tons of time…
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X-Mas Tree with 10 Lines of R Code
Besides the many negative aspects of going through a pandemic, there are also certain positive ones like having time to write short blog posts like this. This one picks up a topic that was intensively discussed a couple of years ago on Wolfram’s page: Namely that the damped sine wave f(t) = t sin(t) can…
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Random Forests with Monotonic Constraints
“R Python” continued… Random forests with monotonic constraints
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SHAP Analysis in 9 Lines
This post shows how to make very generic and quick SHAP interpretations of XGBoost and LightGBM models.
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Strong Random Forests with XGBoost
“R Python” continued… Strong random forests with XGBoost