Sensor

class capymoa.datasets.Sensor

Bases: _DownloadableARFF

Sensor stream is a classification problem based on indoor sensor data.

• Number of instances: 2,219,803

• Number of attributes: 5

• Number of classes: 54

The stream contains temperature, humidity, light, and sensor voltage collected from 54 sensors deployed in Intel Berkeley Research Lab. The classification objective is to predict the sensor ID.

References:

1. https://www.cse.fau.edu/~xqzhu/stream.html

__init__(

directory: str | Path = get_download_dir(),

auto_download: bool = True,

file_type: Literal['arff', 'csv'] = 'arff',

)

Setup a stream from a dataset file and optionally download it if missing.

Parameters:

• directory – Where downloads are stored. Defaults to capymoa.datasets.get_download_dir().

• auto_download – Download the dataset if it is missing.

• file_type – Download either the "arff" or "csv" dataset asset.

__iter__() → Iterator[_AnyInstance]

Get an iterator over the stream.

This will NOT restart the stream if it has already been iterated over. Please use the restart() method to restart the stream.

Yield:

An iterator over the stream.

__next__() → _AnyInstance

Get the next instance in the stream.

Returns:

The next instance in the stream.

cli_help() → str

Return a help message

get_moa_stream() → InstanceStream | None

Get the MOA stream object if it exists.

get_schema() → Schema

Return the schema of the stream.

has_more_instances() → bool

Return True if the stream have more instances to read.

next_instance()

Return the next instance in the stream.

Raises:

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()

Restart the stream to read instances from the beginning.

classmethod to_stream(path: Path) → Stream

Convert the downloaded and unpacked dataset into a datastream.

moa_stream: _InstanceStream | None

schema: Schema

stream: Stream