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c45741a67b
* support latest xgboost version * Update test_classification.py * Update Exists problems when installing xgb1.6.1 in py3.6 * cleanup * xgboost version * remove time_budget_s in test * remove redundancy * stop support of python 3.6 Co-authored-by: zsk <shaokunzhang529@gmail.com> Co-authored-by: Qingyun Wu <qingyun.wu@psu.edu>
69 lines
1.1 KiB
Markdown
69 lines
1.1 KiB
Markdown
# Installation
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FLAML requires **Python version >= 3.7**. It can be installed from pip:
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```bash
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pip install flaml
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```
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or conda:
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```
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conda install flaml -c conda-forge
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```
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FLAML has a .NET implementation as well from [ML.NET Model Builder](https://dotnet.microsoft.com/apps/machinelearning-ai/ml-dotnet/model-builder) in [Visual Studio](https://visualstudio.microsoft.com/) 2022.
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## Optional Dependencies
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### Notebook
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To run the [notebook examples](https://github.com/microsoft/FLAML/tree/main/notebook),
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install flaml with the [notebook] option:
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```bash
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pip install flaml[notebook]
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```
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### Extra learners
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* catboost
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```bash
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pip install flaml[catboost]
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```
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* vowpal wabbit
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```bash
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pip install flaml[vw]
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```
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* time series forecaster: prophet, statsmodels
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```bash
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pip install flaml[forecast]
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```
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* natural language processing: transformers
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```bash
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pip install flaml[nlp]
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```
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### Distributed tuning
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* ray
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```bash
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pip install flaml[ray]
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```
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* nni
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```bash
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pip install flaml[nni]
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```
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* blendsearch
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```bash
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pip install flaml[blendsearch]
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```
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### Test and Benchmark
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* test
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```bash
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pip install flaml[test]
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```
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* benchmark
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```bash
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pip install flaml[benchmark]
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```
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