Skip to main content

Python package for PyEvalis

Project description

PyEvalis

Overview

PyEvalis is a Python library for building and evaluating machine learning models, specifically focusing on Random Forest and Decision Tree algorithms. It aims to simplify the process of model training and evaluation, making it accessible for both beginners and experienced data scientists.

Features

  • Random Forest: An ensemble learning method for classification and regression that builds multiple decision trees and merges their outputs for improved accuracy.
  • Decision Tree: A straightforward model that uses a tree-like graph of decisions and their possible consequences, ideal for both classification and regression tasks.

Installation

You can install My Package using pip. Run the following command in your terminal:

pip install pyevalis

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

pyevalis-0.0.3.tar.gz (7.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

PyEvalis-0.0.3-py3-none-any.whl (9.9 kB view details)

Uploaded Python 3

File details

Details for the file pyevalis-0.0.3.tar.gz.

File metadata

  • Download URL: pyevalis-0.0.3.tar.gz
  • Upload date:
  • Size: 7.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.4

File hashes

Hashes for pyevalis-0.0.3.tar.gz
Algorithm Hash digest
SHA256 60db0dbaa14a75787271e65943034b7ad579f6d3f71a33c2239d666911d70c81
MD5 441c17e9aef77046bd1c9b9e90cbfe17
BLAKE2b-256 1039f019eb3644b9a0392b9d3bf6491eb36283ad70179fe1aa64ce68aca55fd5

See more details on using hashes here.

File details

Details for the file PyEvalis-0.0.3-py3-none-any.whl.

File metadata

  • Download URL: PyEvalis-0.0.3-py3-none-any.whl
  • Upload date:
  • Size: 9.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.4

File hashes

Hashes for PyEvalis-0.0.3-py3-none-any.whl
Algorithm Hash digest
SHA256 f2a3ab94d088ba8258009459e2159a48ebc7e07c219e29d57c10ec10c3acaebe
MD5 0c4f9533280adb8bc9d912fdc1c5f9a2
BLAKE2b-256 047bd3a49460f796ac9a9ce82d795427a0be48364ff9d125c5e60d84da7eeb63

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