Skip to main content

Python package implementing the dagging method

Project description

https://img.shields.io/travis/chkoar/dagging.svg https://codecov.io/gh/chkoar/dagging/branch/master/graph/badge.svg https://img.shields.io/pypi/v/dagging.svg

Python package implementing the dagging method

  • Free software: 3-clause BSD license

Example

from dagging import DaggingClassifier
from sklearn.datasets import load_iris

# Load Iris from from scikit-learn.
X, y = load_iris(True)

model = DaggingClassifier(n_estimators=50,
                          voting='hard',
                          random_state=0)

# Train the model.
model.fit(X,y)

# Accuracy
print(model.score(X, y))

Dependencies

The dependency requirements are based on the last scikit-learn release:

  • scipy
  • numpy
  • scikit-learn

Installation

dagging is currently available on the PyPi’s repository and you can install it via pip:

pip install -U dagging

If you prefer, you can clone it and run the setup.py file. Use the following commands to get a copy from GitHub and install all dependencies:

git clone https://github.com/chkoar/dagging.git
cd dagging
pip install .

Or install using pip and GitHub:

pip install -U git+https://github.com/chkoar/dagging.git

Project details


Download files

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

Files for dagging, version 0.2.2
Filename, size File type Python version Upload date Hashes
Filename, size dagging-0.2.2-py3-none-any.whl (7.5 kB) File type Wheel Python version py3 Upload date Hashes View hashes
Filename, size dagging-0.2.2.tar.gz (26.6 kB) File type Source Python version None Upload date Hashes View hashes

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN SignalFx SignalFx Supporter DigiCert DigiCert EV certificate StatusPage StatusPage Status page