AutoML Streams

An AutoML framework for implementing automated machine learning on data streams architectures in production environments.

Installation

From pip

pip install -U automl-streams

or conda:

conda install automl-streams

Usage

from skmultiflow.trees import HoeffdingTree
from skmultiflow.evaluation import EvaluatePrequential
from automlstreams.streams import KafkaStream

stream = KafkaStream(topic, bootstrap_servers=broker)
stream.prepare_for_use()
ht = HoeffdingTree()
evaluator = EvaluatePrequential(show_plot=True,
                                pretrain_size=200,
                                max_samples=3000)

evaluator.evaluate(stream=stream, model=[ht], model_names=['HT'])

More demonstrations available in the demos directory.

Development

Create and activate a virtualenv for the project:

$ virtualenv .venv
$ source .venv/bin/activate

Install the development dependencies:

$ pip install -e . 

Install the app in "development" mode:

$ python setup.py develop