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| Publisher: | Stata Press |
| Copyright: | 2025 |
| ISBN-13: | 978-1-59718-451-9 |
| Pages: | 361 |
Suggested citation:
StataCorp. 2025. Stata 19 Machine Learning in Stata Using H2O Reference Manual. College Station, TX: Stata Press.
| Intro | Introduction to machine learning and ensemble decision trees |
| h2oml | Introduction to commands for Stata integration with H2O machine learning |
| H2O setup | Prepare data for H2O analysis in Stata |
| h2oml gbm | Gradient boosting machine for regression and classification |
| h2oml gbbinclass | Gradient boosting binary classification |
| h2oml gbmulticlass | Gradient boosting multiclass classification |
| h2oml gbregress | Gradient boosting regression |
| h2oml rf | Random forest for regression and classification |
| h2oml rfbinclass | Random forest binary classification |
| h2oml rfmulticlass | Random forest multiclass classification | h2oml rfregress | Random forest regression |
| h2oml postestimation | Postestimation tools for h2oml gbm and h2oml rf |
| h2omlest | Store and restore H2OML estimation results |
| h2omlestat aucmulticlass | Display AUC and AUCPR after multiclass classification |
| h2omlestat confmatrix | Display confusion matrix |
| h2omlestat cvsummary | Display cross-validation summary |
| h2omlestat gridsummary | Display grid-search summary |
| h2omlestat hitratio | Display hit-ratio table |
| h2omlestat metrics | Display performance metrics |
| h2omlestat threshmetric | Display threshold-based metrics for binary classification |
| h2omlexplore | Explore models after grid search |
| h2omlgof | Compare goodness of fit for machine learning models |
| h2omlgraph ice | Produce individual conditional expectation plot |
| h2omlgraph pdp | Produce partial dependence plot |
| h2omlgraph prcurve | Produce precision–recall curve plot |
| h2omlgraph roc | Produce ROC curve plot |
| h2omlgraph scorehistory | Produce score history plot |
| h2omlgraph shapsummary | Produce SHAP beeswarm plot |
| h2omlgraph shapvalues | Produce SHAP values plot for individual observations |
| h2omlgraph varimp | Produce variable importance plot |
| h2omlpostestframe | Specify frame for postestimation analysis |
| h2omlselect | Select model after grid search |
| h2omltree | Save decision tree DOT file and display rule set |
| DOT extension | Handling DOT files |
| encode_option | Encoding schemes for categorical predictors |
| metric_option | Classification and regression metrics |
| H2O option mapping | Mapping of H2OML estimation options to H2O |
| H2O reproducibility | Reproducibility in H2O |
| Glossary | |
| Subject and author index |
