CLI is not most developed interface. Putting them into correct directory can help new users to avoid it as most of the use cases are from a language binding.
28 lines
1.1 KiB
Markdown
28 lines
1.1 KiB
Markdown
Distributed XGBoost Training
|
|
============================
|
|
This is an tutorial of Distributed XGBoost Training.
|
|
Currently xgboost supports distributed training via CLI program with the configuration file.
|
|
There is also plan push distributed python and other language bindings, please open an issue
|
|
if you are interested in contributing.
|
|
|
|
Build XGBoost with Distributed Filesystem Support
|
|
-------------------------------------------------
|
|
To use distributed xgboost, you only need to turn the options on to build
|
|
with distributed filesystems(HDFS or S3) in cmake.
|
|
|
|
```
|
|
cmake <path/to/xgboost> -DUSE_HDFS=ON -DUSE_S3=ON -DUSE_AZURE=ON
|
|
```
|
|
|
|
|
|
Step by Step Tutorial on AWS
|
|
----------------------------
|
|
Checkout [this tutorial](https://xgboost.readthedocs.org/en/latest/tutorials/aws_yarn.html) for running distributed xgboost.
|
|
|
|
|
|
Model Analysis
|
|
--------------
|
|
XGBoost is exchangeable across all bindings and platforms.
|
|
This means you can use python or R to analyze the learnt model and do prediction.
|
|
For example, you can use the [plot_model.ipynb](plot_model.ipynb) to visualize the learnt model.
|