Fast Histogram Gradient Boosting for Regression, Classification, and Survival Analysis

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Documentation for package ‘fastgbm’ version 0.6.1

• DESCRIPTION file
• User guides, package vignettes and other documentation
• Package NEWS
• Package README

Help Pages

coef.fastgbm	Tree ensembles have no ordinary regression coefficients
fastgbm	Fit a compact gradient boosting model for survival, regression, or classification
importance	Feature importance (total split gain)
load_fastgbm	Load a serialized fastgbm model
metrics	Evaluation metric for a fitted fastgbm model
pdp	Partial dependence for a fitted fastgbm model
predict.fastgbm	Predict from a fitted fastgbm model
predict.fastgbm_multiclass	Predict from a fitted multiclass fastgbm model
print.fastgbm	Print a fitted fastgbm model
print.fastgbm_multiclass	Print a fitted multiclass fastgbm model
print.summary.fastgbm	Print a fastgbm model summary
save_fastgbm	Save a fitted fastgbm model
summary.fastgbm	Summarize a fitted fastgbm model