Skip to main content

Logistic Regression Model Trainer

GitHub issues GitHub stars GitHub license

这是一个命令行工具,旨在简化逻辑回归模型的训练流程。它支持从命令行接收numpy数组格式的特征和标签数据,训练逻辑回归模型,并提供了生成PMML文件的功能,便于模型的跨平台部署。

特性

  • 简单易用:通过命令行界面快速训练模型。
  • 灵活配置:支持生成PMML模型文件,便于集成到其他系统。
  • 高效模型:基于Scikit-learn的逻辑回归实现,支持大规模数据集。

安装

确保已安装Python 3.8+,然后通过pip安装:

pip install logistic-regression-model-trainer

Metadata

Release files for logistic-regression-model-trainer 0.1.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for logistic-regression-model-trainer 0.1.0
File Size Uploaded Provenance Actions
logistic-regression-model-trainer-0.1.0.tar.gz 1.8 kB Without provenance Details for logistic-regression-model-trainer-0.1.0.tar.gz

Built distribution (wheel)

Table of built distributions (wheels) for logistic-regression-model-trainer 0.1.0
File Interpreter ABI Platform Actions
logistic_regression_model_trainer-0.1.0-py3-none-any.whl Python 3 none any Details for logistic_regression_model_trainer-0.1.0-py3-none-any.whl

Total release size: 3.8 kB

Release files / logistic-regression-model-trainer-0.1.0.tar.gz

Download URL logistic-regression-model-trainer-0.1.0.tar.gz
Size 1.8 kB
Tags Source
SHA-256 checksum
How to use checksums
9e3f3a5f8a536659492f11719d8f568fa89b2940b7d7b2983dd8c7a7a05b63b3
BLAKE2b-256 checksum
How to use checksums
7ad914ad3e27c34c88c3250553a16c72f7c912753a01497f782db9c5070d6c1d
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/5.0.0 CPython/3.9.13

Release files / logistic_regression_model_trainer-0.1.0-py3-none-any.whl

Download URL logistic_regression_model_trainer-0.1.0-py3-none-any.whl
Size 1.9 kB
Tags Python 3
SHA-256 checksum
How to use checksums
11c1eeade8f7c2ab2f2d59f4adf4f3c07121443f0a699488d9f75e8d89d0ac95
BLAKE2b-256 checksum
How to use checksums
f993cdc6e914ef46b277fe0f58cc48afa3e485aa0f910b34b3a2b4b6e5200df8
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/5.0.0 CPython/3.9.13

Security for logistic-regression-model-trainer 0.1.0

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Release history Release notifications | RSS feed

This release

0.1.0 This release

2 release files No provenance

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page