Skip to main content

Toolbox for streaming data.

Project description

Travis Status Coveralls Status CircleCI Status KSSK

stream-learn is a Python package equipped with a procedures to process data streams using estimators with API compatible with scikit-learn.

Documentation

API documentation with set of examples may be found on the documentation page.

Installation

stream-learn is available on the PyPi and you may install it with pip:

pip install stream-learn
import strlearn
from sklearn import neural_network

clf = neural_network.MLPClassifier()
X, y = strlearn.utils.load_arff('toyset.arff')
learner = strlearn.Learner(X, y, clf)
learner.run()

Flow controllers and stream estimators

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

stream-learn-0.3.2.tar.gz (10.4 kB view details)

Uploaded Source

File details

Details for the file stream-learn-0.3.2.tar.gz.

File metadata

  • Download URL: stream-learn-0.3.2.tar.gz
  • Upload date:
  • Size: 10.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for stream-learn-0.3.2.tar.gz
Algorithm Hash digest
SHA256 cf8f3c4bfd3cf0b5f5e310fa3c378c0de62942e50604fa831333b3ca6a8aee79
MD5 332c3baafc49a88e9c1f1c3df378dad5
BLAKE2b-256 13bdf6cea9dda21b58a0221f4f56810f57ba76f1890ba634ab709236057b4505

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page