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About Deep Learning With H20 in R
The document outlines 14 steps for building and evaluating a gradient boosted machine model for churn prediction using the H2O library in R. It includes steps for loading and preparing data, building the GBM model, evaluating model performance on training and test data, interpreting variable importance, and exporting the model.
Detailed Information
| Author: | ['Jerric Lyns John'] |
|---|---|
| Publication Year: | 2019 |
| Pages: | 6 |
| Language: | English |
| Format: | |
| Price: | FREE |
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