# `OSNN`

### *class* capymoa.ssl.OSNN[[source]](https://github.com/adaptive-machine-learning/CapyMOA/blob/3e255b1/src/capymoa/ssl/_osnn.py#L255)

Bases: [`ClassifierSSL`](capymoa.base.ClassifierSSL.md#capymoa.base.ClassifierSSL)

Online Semi-Supervised Neural Network.

Online Semi-Supervised Neural Network (OSNN) <sup>[1](#f0)</sup> is a neural network designed
for semi-supervised learning in non-stationary data streams.

* <a id='f0'>**[1]**</a> R. G. F. Soares and L. L. Minku, “Osnn: An online semisupervised neural network for nonstationary data streams,” IEEE Transactions on Neural Networks and Learning Systems, pp. 1–13, 2021.

#### \_\_init_\_(schema=None, num_center=10, n_out=1, window_size=200, beta=1, gamma=1, optim_steps=200, seed=1)[[source]](https://github.com/adaptive-machine-learning/CapyMOA/blob/3e255b1/src/capymoa/ssl/_osnn.py#L266)

#### *classmethod* from_params(schema: [Any](https://docs.python.org/3/library/typing.html#typing.Any) = None, params: [dict](https://docs.python.org/3/builtins/stdtypes.html#dict)[[str](https://docs.python.org/3/builtins/stdtypes.html#str), [Any](https://docs.python.org/3/library/typing.html#typing.Any)] | [None](https://docs.python.org/3/builtins/constants.html#None) = None, random_seed: [int](https://docs.python.org/3/builtins/functions.html#int) = 1) → [Any](https://docs.python.org/3/library/typing.html#typing.Any)[[source]](https://github.com/adaptive-machine-learning/CapyMOA/blob/3e255b1/src/capymoa/base/_learner_params.py#L170)

Construct an instance from parameters produced by `get_params`.

#### get_params() → [dict](https://docs.python.org/3/builtins/stdtypes.html#dict)[[str](https://docs.python.org/3/builtins/stdtypes.html#str), [Any](https://docs.python.org/3/library/typing.html#typing.Any)][[source]](https://github.com/adaptive-machine-learning/CapyMOA/blob/3e255b1/src/capymoa/base/_learner_params.py#L163)

Return the hyper-parameters captured from the constructor.

#### predict(instance)[[source]](https://github.com/adaptive-machine-learning/CapyMOA/blob/3e255b1/src/capymoa/ssl/_osnn.py#L337)

Predict the label of an instance.

The base implementation calls [`predict_proba()`](#capymoa.ssl.OSNN.predict_proba) and returns the
label with the highest probability.

* **Parameters:**
  **instance** – The instance to predict the label for.
* **Returns:**
  The predicted label or `None` if the classifier is unable
  to make a prediction.

#### predict_proba(instance)[[source]](https://github.com/adaptive-machine-learning/CapyMOA/blob/3e255b1/src/capymoa/ssl/_osnn.py#L329)

Return probability estimates for each label.

* **Parameters:**
  **instance** – The instance to estimate the probabilities for.
* **Returns:**
  An array of probabilities for each label or `None` if the
  classifier is unable to make a prediction.

#### train(instance)[[source]](https://github.com/adaptive-machine-learning/CapyMOA/blob/3e255b1/src/capymoa/ssl/_osnn.py#L296)

Train the classifier with a labeled instance.

* **Parameters:**
  **instance** – The labeled instance to train the classifier with.

#### train_on_unlabeled(instance)[[source]](https://github.com/adaptive-machine-learning/CapyMOA/blob/3e255b1/src/capymoa/ssl/_osnn.py#L299)

#### random_seed *: [int](https://docs.python.org/3/builtins/functions.html#int)*

The random seed for reproducibility.

When implementing a classifier ensure random number generators are seeded.

#### schema *: [Schema](capymoa.stream.Schema.md#capymoa.stream.Schema)*

The schema representing the instances.