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Update part of the docs

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2020-11-24 23:56:16 +08:00
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docs/introduction/quick.rst
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@@ -49,18 +49,19 @@ To kown more about `prepare data`, please refer to `Data Preparation <../compone
Auto Quant Research Workflow
====================================
``Qlib`` provides a tool named ``Estimator`` to run the whole workflow automatically (including building dataset, training models, backtest and evaluation). Users can start an auto quant research workflow and have a graphical reports analysis according to the following steps:
``Qlib`` provides a tool named ``qrun`` to run the whole workflow automatically (including building dataset, training models, backtest and evaluation). Users can start an auto quant research workflow and have a graphical reports analysis according to the following steps:
- Quant Research Workflow:
- Run ``Estimator`` with `estimator_config.yaml` as following.
- Run ``qrun`` with a config file of the LightGBM model `workflow_config_lightgbm.yaml` as following.
.. code-block::
cd examples # Avoid running program under the directory contains `qlib`
estimator -c estimator/estimator_config.yaml
qrun benchmarks/LightGBM/workflow_config_lightgbm.yaml
- Estimator result
The result of ``Estimator`` is as follows, which is also the result of ``Intraday Trading``. Please refer to `Intraday Trading <../component/backtest.html>`_. for more details about the result.
- Workflow result
The result of ``qrun`` is as follows, which is also the result of ``Intraday Trading``. Please refer to `Intraday Trading <../component/backtest.html>`_. for more details about the result.
.. code-block:: python
@@ -77,11 +78,11 @@ Auto Quant Research Workflow
max_drawdown -0.075024
To know more about `Estimator`, please refer to `Estimator: Workflow Management <../component/estimator.html>`_.
To know more about `workflow` and `qrun`, please refer to `Workflow: Workflow Management <../component/workflow.html>`_.
- Graphical Reports Analysis:
- Run ``examples/estimator/analyze_from_estimator.ipynb`` with jupyter notebook
Users can have portfolio analysis or prediction score (model prediction) analysis by run ``examples/estimator/analyze_from_estimator.ipynb``.
- Run ``examples/workflow_by_code.ipynb`` with jupyter notebook
Users can have portfolio analysis or prediction score (model prediction) analysis by run ``examples/workflow_by_code.ipynb``.
- Graphical Reports
Users can get graphical reports about the analysis, please refer to `Aanalysis: Evaluation & Results Analysis <../component/report.html>`_ for more details.
@@ -90,4 +91,4 @@ Auto Quant Research Workflow
Custom Model Integration
===============================================
``Qlib`` provides ``lightGBM`` and ``Dnn`` model as the baseline of ``Interday Model``. In addition to the default model, users can integrate their own custom models into ``Qlib``. If users are interested in the custom model, please refer to `Custom Model Integration <../start/integration.html>`_.
``Qlib`` provides several models such as ``lightGBM`` and ``DNN`` model as the baseline of ``Interday Model``. In addition to the default model, users can integrate their own custom models into ``Qlib``. If users are interested in the custom model, please refer to `Custom Model Integration <../start/integration.html>`_.