ngboost-release

v0.3.12.post2

It is just a workaround to fix the current ngboost package issue. See: https://github.com/stanfordmlgroup/ngboost/issues/283 For more information about how to use this package see README

Latest version published 2 years ago

License: Apache-2.0

PyPI

GitHub

Package Health Score

45 / 100

security
Security review needed
popularity
Small
maintenance
Inactive
community
Sustainable

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classifier
51

Popularity

Small

GitHub Stars: 1.63K
Forks: 213
Contributors: 40

Direct Usage Popularity

Based on project statistics from the GitHub repository for the PyPI package ngboost-release, we found that it has been starred 1,631 times.

Security

Security review needed

Security and license risk for latest version

Release Date: Sep 9, 2022
Direct Vulnerabilities: 0
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0
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Indirect Vulnerabilities: 0
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License Risk: 0
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All security vulnerabilities belong to production dependencies of direct and indirect packages.

License

Apache-2.0

Security Policy

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Maintenance

Inactive

Commit Frequency

Open Issues: 41
Open PR: 7
Last Release: 2 years ago
Last Commit: 9 months ago

Further analysis of the maintenance status of ngboost-release based on released PyPI versions cadence, the repository activity, and other data points determined that its maintenance is Inactive.

An important project maintenance signal to consider for ngboost-release is that it hasn't seen any new versions released to PyPI in the past 12 months, and could be considered as a discontinued project, or that which receives low attention from its maintainers.

In the past month we didn't find any pull request activity or change in issues status has been detected for the GitHub repository.

Community

Sustainable

Readme: Yes
Contributing.md: No
Code of Conduct: No
Contributors: 40
Funding: No

With more than 10 contributors for the ngboost-release repository, this is possibly a sign for a growing and inviting community.

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Package

Python Versions Compatibility: >=3.6,<4.0

Age: 2 years
Latest Release: 2 years ago
Dependencies: 5 Direct / 28 Total
Versions: 3
Maintainers: 1
Wheels: OS Independent

Readme

NGBoost: Natural Gradient Boosting for Probabilistic Prediction

Python package

ngboost is a Python library that implements Natural Gradient Boosting, as described in "NGBoost: Natural Gradient Boosting for Probabilistic Prediction". It is built on top of Scikit-Learn, and is designed to be scalable and modular with respect to choice of proper scoring rule, distribution, and base learner. A didactic introduction to the methodology underlying NGBoost is available in this slide deck.

Installation

via pip

pip install --upgrade ngboost

via conda-forge

conda install -c conda-forge ngboost

Usage

Probabilistic regression example on the Boston housing dataset:

from ngboost import NGBRegressor

from sklearn.datasets import load_boston
from sklearn.model_selection import train_test_split
from sklearn.metrics import mean_squared_error

X, Y = load_boston(True)
X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=0.2)

ngb = NGBRegressor().fit(X_train, Y_train)
Y_preds = ngb.predict(X_test)
Y_dists = ngb.pred_dist(X_test)

# test Mean Squared Error
test_MSE = mean_squared_error(Y_preds, Y_test)
print('Test MSE', test_MSE)

# test Negative Log Likelihood
test_NLL = -Y_dists.logpdf(Y_test).mean()
print('Test NLL', test_NLL)

Details on available distributions, scoring rules, learners, tuning, and model interpretation are available in our user guide, which also includes numerous usage examples and information on how to add new distributions or scores to NGBoost.

License

Apache License 2.0.

Reference

Tony Duan, Anand Avati, Daisy Yi Ding, Khanh K. Thai, Sanjay Basu, Andrew Y. Ng, Alejandro Schuler. 2019. NGBoost: Natural Gradient Boosting for Probabilistic Prediction. arXiv

ngboost-release dependencies

lifelines numpy scikit-learn scipy tqdm

FAQs

What is ngboost-release?

It is just a workaround to fix the current ngboost package issue. See: https://github.com/stanfordmlgroup/ngboost/issue... Visit Snyk Advisor to see a full health score report for ngboost-release, including popularity, security, maintenance & community analysis.

Is ngboost-release popular?

The python package ngboost-release receives a total of 40 weekly downloads. As such, ngboost-release popularity was classified as small. Visit the popularity section on Snyk Advisor to see the full health analysis.

Is ngboost-release well maintained?

We found indications that ngboost-release is an Inactive project. See the full package health analysis to learn more about the package maintenance status.

Is ngboost-release safe to use?

While scanning the latest version of ngboost-release, we found that a security review is needed. A total of 0 vulnerabilities or license issues were detected. See the full security scan results.

Last updated on 30 October-2024, at 23:45 (UTC).

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Readme

NGBoost: Natural Gradient Boosting for Probabilistic Prediction

Installation

Usage

License

Reference

ngboost-release dependencies

FAQs

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