ClassificaIO
This repository contains ClassificaIO, a Python package that provides a graphical user (GUI) for machine learning classification algorithms from scikit-learn.
ClassificaIO Installation Instructions
A. INSTALLATION
Recommended Pre-Installation Requirements
- To install ClassificaIO on any platform you need:
A Python distribution - ClassificaIO was built usining Anaconda distribution, python 3.6.
Installation Instructions
1. Mac or Windows
To install the current ClassificaIO release use pip:
pip install ClassificaIOAlternatively, you can install directly from github using:
pip install git+https://github.com/gmiaslab/ClassificaIO/2. Linux
First install the current release of tkinter and pip
sudo apt-get install python3-tk
sudo apt-get install python3-pipTo install the current ClassificaIO release use pip
pip3 install ClassificaIOAlternatively, you can install directly from github using:
pip3 install git+https://github.com/gmiaslab/ClassificaIO/B. RUNNING ClassificaIO
After installation you can run:
>>> from ClassificaIO import ClassificaIO
>>> ClassificaIO.gui()C. DOCUMENTATION
Documentation for ClassificaIO is provided in the manual, available online at: * https://github.com/gmiaslab/manuals/blob/master/ClassificaIO/ClassificaIO_UserManual.pdf
The manual can also be accessed directly through the Help menu in ClassificaIO that points to the above location.
D. LICENSING
ClassificaIO is provided under an MIT license.
E. OTHER CONTACT INFORMATION
Contributions: Raeuf Roushangar, George I. Mias
G.MiasLab (https://georgemias.org)
e-mail: gmiaslab@gmail.com
twitter: @gmiaslab
2 maintainers
Metadata
2 maintainers
Release files for ClassificaIO 1.1.5.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| ClassificaIO-1.1.5.1.tar.gz | 332.2 kB | Details |
Release files / ClassificaIO-1.1.5.1.tar.gz
| Download URL | ClassificaIO-1.1.5.1.tar.gz |
|---|---|
| Size | 332.2 kB |
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