Assisted Model Building, using Surrogate Black-Box Models to Train Interpretable Spline Based Additive Models


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Documentation for package ‘xspliner’ version 0.0.4

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xspliner-package Easy way for approximating data with splines.
aic Statistics used for better linear model selection
approx_with_monotonic_spline Approximate spline on data
approx_with_spline Approximate spline on data
build_xspliner Helper function for building GLM object with transformed variables.
hoslem Statistics used for better linear model selection
log_msg Helper function to print out log messages
model_surrogate_xspliner Builds predictive model based GLM.
plot.xspliner Plot method for 'xspliner' model
plot_model_comparison Plot models comparison
plot_variable_transition Plot variable profile
predict.xspliner Predict xspliner method
print.xspliner Print method for xspliner object
stats Statistics used for better linear model selection
summary.xspliner Summary method for xspliner object
transition Extract variable transformation from xspliner
transition.xspliner Extract variable transformation from xspliner
xf_opts_default Default parameters for transition methods
xspline Builds predictive model based GLM.
xspline.default Builds predictive model based GLM.
xspline.explainer Builds predictive model based GLM.
xspline.formula Builds predictive model based GLM.
xs_opts_default Default parameters for transition methods