# `RandomRBFGenerator`

### *class* capymoa.stream.generator.RandomRBFGenerator[[source]](https://github.com/adaptive-machine-learning/CapyMOA/blob/3e255b1/src/capymoa/stream/generator.py#L404)

Bases: [`MOAStream`](capymoa.stream.MOAStream.md#capymoa.stream.MOAStream)

An Random RBF Generator

```pycon
>>> from capymoa.stream.generator import RandomRBFGenerator
...
>>> stream = RandomRBFGenerator()
>>> stream.next_instance()
LabeledInstance(
    Schema(generators.RandomRBFGenerator ),
    x=[0.21  1.01  0.092 0.272 0.45  0.226 0.212 0.373 0.583 0.297],
    y_index=1,
    y_label='class2'
)
>>> stream.next_instance().x
array([0.68807095, 0.62508298, 0.36161375, 0.29484898, 0.46067958,
       0.83491016, 0.69794979, 0.75702471, 0.79436834, 0.7605141 ])
```

#### \_\_init_\_(model_random_seed: [int](https://docs.python.org/3/builtins/functions.html#int) = 1, instance_random_seed: [int](https://docs.python.org/3/builtins/functions.html#int) = 1, number_of_classes: [int](https://docs.python.org/3/builtins/functions.html#int) = 2, number_of_attributes: [int](https://docs.python.org/3/builtins/functions.html#int) = 10, number_of_centroids: [int](https://docs.python.org/3/builtins/functions.html#int) = 50)[[source]](https://github.com/adaptive-machine-learning/CapyMOA/blob/3e255b1/src/capymoa/stream/generator.py#L423)

Construct a Random RBF Generator .

* **Parameters:**
  * **instance_random_seed** – Seed for random generation of instances, defaults to 1
  * **number_of_classes** – The number of classes of the generated instances, defaults to 2
  * **number_of_attributes** – The number of attributes of the generated instances, defaults to 10
  * **number_of_drifting_centroids** – The number of drifting attributes, defaults to 2

#### \_\_iter_\_() → [Self](https://docs.python.org/3/library/typing.html#typing.Self)[[source]](https://github.com/adaptive-machine-learning/CapyMOA/blob/3e255b1/src/capymoa/stream/_stream.py#L356)

Get an iterator over the stream.

This will NOT restart the stream if it has already been iterated over.
Please use the [`restart()`](#capymoa.stream.generator.RandomRBFGenerator.restart) method to restart the stream.

* **Yield:**
  An iterator over the stream.

#### \_\_next_\_() → \_AnyInstance[[source]](https://github.com/adaptive-machine-learning/CapyMOA/blob/3e255b1/src/capymoa/stream/_stream.py#L366)

Get the next instance in the stream.

* **Returns:**
  The next instance in the stream.

#### cli_help() → [str](https://docs.python.org/3/builtins/stdtypes.html#str)[[source]](https://github.com/adaptive-machine-learning/CapyMOA/blob/3e255b1/src/capymoa/stream/_stream.py#L466)

Return cli help string for the stream.

#### get_moa_stream() → InstanceStream | [None](https://docs.python.org/3/builtins/constants.html#None)[[source]](https://github.com/adaptive-machine-learning/CapyMOA/blob/3e255b1/src/capymoa/stream/_stream.py#L502)

Get the MOA stream object if it exists.

#### get_schema() → [Schema](capymoa.stream.Schema.md#capymoa.stream.Schema)[[source]](https://github.com/adaptive-machine-learning/CapyMOA/blob/3e255b1/src/capymoa/stream/_stream.py#L498)

Return the schema of the stream.

#### has_more_instances() → [bool](https://docs.python.org/3/builtins/functions.html#bool)[[source]](https://github.com/adaptive-machine-learning/CapyMOA/blob/3e255b1/src/capymoa/stream/_stream.py#L474)

Return True if the stream have more instances to read.

#### next_instance() → \_AnyInstance[[source]](https://github.com/adaptive-machine-learning/CapyMOA/blob/3e255b1/src/capymoa/stream/_stream.py#L478)

Return the next instance in the stream.

* **Raises:**
  [**ValueError**](https://docs.python.org/3/builtins/exceptions.html#ValueError) – If the machine learning task is neither a regression
  nor a classification task.
* **Returns:**
  A labeled instances or a regression depending on the schema.

#### restart()[[source]](https://github.com/adaptive-machine-learning/CapyMOA/blob/3e255b1/src/capymoa/stream/_stream.py#L506)

Restart the stream to read instances from the beginning.