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Update docs

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Jactus
2020-11-30 18:54:31 +08:00
committed by you-n-g
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commit 29f12e857f
22 changed files with 180 additions and 159 deletions
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docs/start/integration.rst
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@@ -19,8 +19,8 @@ The Custom models need to inherit `qlib.model.base.Model <../reference/api.html#
- Override the `__init__` method
- ``Qlib`` passes the initialized parameters to the \_\_init\_\_ method.
- The parameter must be consistent with the hyperparameters in the configuration file.
- Code Example: In the following example, the hyperparameter filed of the configuration file should contain parameters such as `loss:mse`.
- The hyperparameters of model in the configuration must be consistent with those defined in the `__init__` method.
- Code Example: In the following example, the hyperparameters of model in the configuration file should contain parameters such as `loss:mse`.
.. code-block:: Python
def __init__(self, loss='mse', **kwargs):
@@ -31,9 +31,9 @@ The Custom models need to inherit `qlib.model.base.Model <../reference/api.html#
self._model = None
- Override the `fit` method
- ``Qlib`` calls the fit method to train the model
- The parameters must include training feature `dataset`.
- The parameters could include some optional parameters with default values, such as `num_boost_round = 1000` for `GBDT`.
- ``Qlib`` calls the fit method to train the model.
- The parameters must include training feature `dataset`, which is designed in the interface.
- The parameters could include some `optional` parameters with default values, such as `num_boost_round = 1000` for `GBDT`.
- Code Example: In the following example, `num_boost_round = 1000` is an optional parameter.
.. code-block:: Python
@@ -69,7 +69,7 @@ The Custom models need to inherit `qlib.model.base.Model <../reference/api.html#
)
- Override the `predict` method
- The parameters must include training feature `dataset`, which will be userd to get the test dataset.
- The parameters must include the parameter `dataset`, which will be userd to get the test dataset.
- Return the `prediction score`.
- Please refer to `Model API <../reference/api.html#module-qlib.model.base>`_ for the parameter types of the fit method.
- Code Example: In the following example, users need to use `LightGBM` to predict the label(such as `preds`) of test data `x_test` and return it.
@@ -81,8 +81,9 @@ The Custom models need to inherit `qlib.model.base.Model <../reference/api.html#
x_test = dataset.prepare("test", col_set="feature", data_key=DataHandlerLP.DK_I)
return pd.Series(self.model.predict(x_test.values), index=x_test.index)
- Override the `finetune` method
- The parameters must include training feature `dataset`.
- Override the `finetune` method (Optional)
- This method is optional to the users, and when users one to use this method on their own models, they should inherit the ``ModelFT`` base class, which includes the interface of `finetune`.
- The parameters must include the parameter `dataset`.
- Code Example: In the following example, users will use `LightGBM` as the model and finetune it.
.. code-block:: Python