Skip to main content
Pre-release

This release is a pre-release and may not be stable for production use.

ml-utils

ml_utils is a Python package that provides a suite of plotting functions to visualize machine learning models and data. It offers intuitive and customizable plots to aid in model evaluation and data analysis.

Features

  • Model Evaluation Plots:
    • Confusion matrices
    • ROC curves
    • Precision-recall curves
  • Data Visualization:
    • Heatmaps
    • Pair plots
    • Feature importance plots
  • Compatibility:
    • Integrates seamlessly with popular machine learning libraries like scikit-learn and TensorFlow.

Installation

You can install ml_utils using pip:

pip install ml_utils

Metadata

Release files for rlax-utils 0.0.1a0

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

Source distribution (sdist)

Source distribution for rlax-utils 0.0.1a0
File Size Uploaded
rlax_utils-0.0.1a0.tar.gz 4.3 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for rlax-utils 0.0.1a0
File Interpreter ABI Platform
rlax_utils-0.0.1a0-py3-none-any.whl Python 3 none any Details

Total release size: 8.3 kB

Release files / rlax_utils-0.0.1a0.tar.gz

Download URL rlax_utils-0.0.1a0.tar.gz
Size 4.3 kB
Tags Source
SHA-256 checksum
How to use checksums
6a7e787f3b156b55e0da5d3b43dac657d0eb4739cec2adf9d985930a1e998fba
BLAKE2b-256 checksum
How to use checksums
0b3cded82c4c48161fc067f7717b73927f82082dc7f790d7b71e9169e913b757
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.0.1 CPython/3.12.8

Release files / rlax_utils-0.0.1a0-py3-none-any.whl

Download URL rlax_utils-0.0.1a0-py3-none-any.whl
Size 4.0 kB
Tags Python 3
SHA-256 checksum
How to use checksums
3cc51b9fa385bf6f52061b8aae108584f6c1b1dc09c70d9c5cb3e20c2980461d
BLAKE2b-256 checksum
How to use checksums
fa06c86707720feeaddb20af1819cfea8c913414f9d4f3bdcf2b5ecfb299bc00
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.0.1 CPython/3.12.8

Release history Release notifications | RSS feed

This release

0.0.1a0 This release

2 release files

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