77 lines
5.6 KiB
Plaintext
77 lines
5.6 KiB
Plaintext
---
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title: MulticlassExtension
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description: API reference for qiskit.aqua.components.multiclass_extensions.MulticlassExtension
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in_page_toc_min_heading_level: 1
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python_api_type: class
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python_api_name: qiskit.aqua.components.multiclass_extensions.MulticlassExtension
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---
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<span id="qiskit-aqua-components-multiclass-extensions-multiclassextension" />
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# qiskit.aqua.components.multiclass\_extensions.MulticlassExtension
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<Class id="qiskit.aqua.components.multiclass_extensions.MulticlassExtension" isDedicatedPage={true} github="https://github.com/qiskit-community/qiskit-aqua/tree/stable/0.8/qiskit/aqua/components/multiclass_extensions/multiclass_extension.py" signature="MulticlassExtension" modifiers="class">
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Base class for multiclass extension.
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This method should initialize the module and use an exception if a component of the module is not available.
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### \_\_init\_\_
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<Function id="qiskit.aqua.components.multiclass_extensions.MulticlassExtension.__init__" signature="__init__()" modifiers="abstract">
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Initialize self. See help(type(self)) for accurate signature.
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</Function>
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## Methods
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| | |
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| -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| [`__init__`](#qiskit.aqua.components.multiclass_extensions.MulticlassExtension.__init__ "qiskit.aqua.components.multiclass_extensions.MulticlassExtension.__init__")() | Initialize self. |
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| [`predict`](#qiskit.aqua.components.multiclass_extensions.MulticlassExtension.predict "qiskit.aqua.components.multiclass_extensions.MulticlassExtension.predict")(x) | Applying multiple estimators for prediction. |
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| [`set_estimator`](#qiskit.aqua.components.multiclass_extensions.MulticlassExtension.set_estimator "qiskit.aqua.components.multiclass_extensions.MulticlassExtension.set_estimator")(estimator\_cls\[, params]) | Called internally to set `Estimator` and parameters :type estimator\_cls: `Callable`\[\[`List`], `Estimator`] :param estimator\_cls: An `Estimator` class :type params: `Optional`\[`List`] :param params: Parameters for the estimator |
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| [`test`](#qiskit.aqua.components.multiclass_extensions.MulticlassExtension.test "qiskit.aqua.components.multiclass_extensions.MulticlassExtension.test")(x, y) | Testing multiple estimators each for distinguishing a pair of classes. |
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| [`train`](#qiskit.aqua.components.multiclass_extensions.MulticlassExtension.train "qiskit.aqua.components.multiclass_extensions.MulticlassExtension.train")(x, y) | Training multiple estimators each for distinguishing a pair of classes. |
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### predict
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<Function id="qiskit.aqua.components.multiclass_extensions.MulticlassExtension.predict" signature="predict(x)" modifiers="abstract">
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Applying multiple estimators for prediction.
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**Parameters**
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**x** (*numpy.ndarray*) – input points
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</Function>
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### set\_estimator
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<Function id="qiskit.aqua.components.multiclass_extensions.MulticlassExtension.set_estimator" signature="set_estimator(estimator_cls, params=None)">
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Called internally to set `Estimator` and parameters :type estimator\_cls: `Callable`\[\[`List`], `Estimator`] :param estimator\_cls: An `Estimator` class :type params: `Optional`\[`List`] :param params: Parameters for the estimator
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**Return type**
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`None`
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</Function>
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### test
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<Function id="qiskit.aqua.components.multiclass_extensions.MulticlassExtension.test" signature="test(x, y)" modifiers="abstract">
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Testing multiple estimators each for distinguishing a pair of classes.
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**Parameters**
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* **x** (*numpy.ndarray*) – input points
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* **y** (*numpy.ndarray*) – input labels
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</Function>
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### train
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<Function id="qiskit.aqua.components.multiclass_extensions.MulticlassExtension.train" signature="train(x, y)" modifiers="abstract">
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Training multiple estimators each for distinguishing a pair of classes.
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**Parameters**
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* **x** (*numpy.ndarray*) – input points
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* **y** (*numpy.ndarray*) – input labels
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</Function>
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</Class>
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