From the course: The Modern Stata Playbook: Critical Enhancements You Need to Know
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Machine learning with H2O integration - Stata Tutorial
From the course: The Modern Stata Playbook: Critical Enhancements You Need to Know
Machine learning with H2O integration
H2O is an open source distributed platform developed by the company H2O.AI. It's designed for building and deploying advanced machine learning methods and AI models and you can now access H2O machine learning models directly via Stata. Specifically, Stata allows you to use this external platform to implement gradient-boosted machine learning and random forest machine learning. You need to understand three types of commands to use H2O within Stata. To start and stop an H2O cluster, use the H2O init command, which launches a local H2O cluster, and use the H2O shutdown command to stop it when you're done. Then you'll need to use the underscore H2O frame commands to move and manage data between your local version of Stata and the H2O cluster. Finally, to train models, assess models, and predict data, you need to use the H2O ML commands. Some key commands are shown in this table, but there are many more, and it is recommended that you carefully read the associated help file. Let's have a…
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