River function

OnlineML(client, stream_ids, model, prediction_type=RuntimeType.STRING.value, supervised=False, target_label=None, on_start=lambda self, context: None, on_event=lambda self, event, streamId: None, on_stop=lambda self: None)

Wrapper class to enable an easy usage for Online Machine Learning models of the River library.

It creates a StreamPipesFunction to train a model with the incoming events of a data stream and creates an output data stream that publishes the prediction to StreamPipes.

PARAMETER	DESCRIPTION
client	The client for the StreamPipes API. TYPE: StreamPipesClient
stream_ids	The ids of the data stream to train the model. TYPE: List[str]
model	The model to train. It meant to be a River model/pipeline, but can be every model with a 'learn_one' and 'predict_one' methode. TYPE: Any
prediction_type	The data type of the prediction. Is only needed when you continue to work with the prediction in StreamPipes. TYPE: str DEFAULT: RuntimeType.STRING.value
supervised	Define if the model is supervised or unsupervised. TYPE: bool DEFAULT: False
target_label	Define the name of the target attribute if the model is supervised. TYPE: Optional[str] DEFAULT: None
on_start	A function to be called when this StreamPipesFunction gets started. TYPE: Callable[[Any, FunctionContext], None] DEFAULT: lambda self, context: None
on_event	A function to be called when this StreamPipesFunction receives an event. TYPE: Callable[[Any, Dict[str, Any], str], None] DEFAULT: lambda self, event, streamId: None
on_stop	A function to be called when this StreamPipesFunction gets stopped. TYPE: Callable[[Any], None] DEFAULT: lambda self: None

set_learning(learning)

Start or stop the training of the model.

PARAMETER	DESCRIPTION
learning	Defines if the training should be continued TYPE: bool

start()

Registers the function and starts the training.

stop()

Stops the function and ends the training forever.

RiverFunction(function_definition, stream_ids, model, supervised, target_label, on_start, on_event, on_stop)

Bases: StreamPipesFunction

Implementation of a StreamPipesFunction to enable an easy usage for Online Machine Learning models of the River library.

The function trains the model with the incoming events and publishes the prediction to an output data stream.

PARAMETER	DESCRIPTION
function_definition	The function definition which contains the output stream. TYPE: FunctionDefinition
stream_ids	The ids of the data stream to train the model. TYPE: List[str]
model	The model to train. It meant to be a River model/pipeline, but can be every model with a 'learn_one' and 'predict_one' method. TYPE: Any
supervised	Define if the model is supervised or unsupervised. TYPE: bool
target_label	Define the name of the target attribute if the model is supervised. TYPE: Optional[str]
on_start	A function to be called when this StreamPipesFunction gets started. TYPE: Callable[[Any, FunctionContext], None]
on_event	A function to be called when this StreamPipesFunction receives an event. TYPE: Callable[[Any, Dict[str, Any], str], None]
on_stop	A function to be called when this StreamPipesFunction gets stopped. TYPE: Callable[[Any], None]

onEvent(event, streamId)

Trains the model with the incoming events and sends the prediction back to StreamPipes.

PARAMETER	DESCRIPTION
event	The incoming event that serves as input for the function TYPE: Dict[str, Any]
streamId	Identifier of the corresponding data stream TYPE: str

RETURNS	DESCRIPTION
None

onServiceStarted(context)

Executes the on_start method of the function.

PARAMETER	DESCRIPTION
context	The functions' context TYPE: FunctionContext

RETURNS	DESCRIPTION
None

onServiceStopped()

Executes the on_stop function.

requiredStreamIds()

Returns the stream ids required by this function.

RETURNS	DESCRIPTION
stream_ids	List of stream ids required by the function TYPE: List[str]