Interactively Explore Local Explanations with the Radial Tour
Assure a full length logical index
cheem
Preprocessing for use in shiny app
Suggest a color and fill scale.
Check if a vector contains non-numeric character
Development message
Linked plotly display, global view of data and attribution space.
Create the plot data.frame for the global linked plotly display.
The legwork behind the scenes for the global view
Evaluate if development
Check if a vector is discrete
Check if a vector diverges a value
Linear function to help set alpha opacity
Logistic function to help set alpha opacity
Extract higher level model performance statistics
The type of model for a given Y variable
Adds the distribution of the row local attributions to a ggtour
Cheem tour; 1D manual tour on the selected attribution
Objects exported from other packages
Draw new samples from the supplied data given its mean and covariances...
Runs a shiny app demonstrating manual tours
Subset a cheem list
Suggest a 1D Basis
Suggest a manipulation variable
Given a non-linear model, calculate the local explanation. We purpose view the data space, explanation space, and model residuals as ensemble graphic interactive on a shiny application. After an observation of interest is identified, the normalized variable importance of the local explanation is used as a 1D projection basis. The support of the local explanation is then explored by changing the basis with the use of the radial tour <doi:10.32614/RJ-2020-027>; <doi:10.1080/10618600.1997.10474754>.
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