Orange, a component-based data mining framework.

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  • License: GNU General Public License v3 or later (GPLv3+) (GPLv3+)
  • Author: Bioinformatics Laboratory, FRI UL
  • Tags data mining, machine learning, artificial intelligence
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Project description

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[Orange] is a component-based data mining software. It includes a range of data visualization, exploration, preprocessing and modeling techniques. It can be used through a nice and intuitive user interface or, for more advanced users, as a module for the Python programming language.

This is a development version of Orange 3. The stable version 2.7 is still available ([binaries] and [sources]).

[Orange]: http://orange.biolab.si/ [binaries]: http://orange.biolab.si/orange2/ [sources]: https://github.com/biolab/orange

Installing

Orange requires Python 3.4 or newer. To build it and install it in a development environment, run:

# Install some build requirements via your system’s package manager sudo apt install virtualenv git build-essential python3-dev

# Create a separate Python environment for Orange and its dependencies … virtualenv –python=python3 –system-site-packages orange3venv # … and make it the active one source orange3venv/bin/activate

# Clone the repository and move into it git clone https://github.com/biolab/orange3.git cd orange3

# Install Qt dependencies for the GUI pip install PyQt5 # Of if Python <= 3.4 and/or with package manager # sudo apt install python3-pyqt4

# Install other minimum required dependencies pip install -r requirements-core.txt # For Orange Python library pip install -r requirements-gui.txt # For Orange GUI

pip install -r requirements-sql.txt # To use SQL support pip install -r requirements-opt.txt # Optional dependencies, may fail

# Finally install Orange in editable/development mode. pip install -e .

Installation of SciPy and qt-graph-helpers is sometimes challenging because of their non-python dependencies that have to be installed manually. More detailed, if mostly obsolete, guides for some platforms can be found in the [wiki].

[wiki]: https://github.com/biolab/orange3/wiki

Anaconda Installation

First, install [Anaconda] for your OS (Python version 3.5+). Create virtual environment for Orange:

conda create python=3 –name orange3

In your Anaconda Prompt add conda-forge to your channels:

conda config –add channels conda-forge

This will enable access to the latest Orange release. Then install Orange3:

conda install orange3

[Anaconda]: https://www.continuum.io/downloads

Starting Orange GUI

Orange GUI requires PyQt, which is not pip-installable in Python 3. You have to download and install it system-wide. Make sure that the virtual environment for orange is created with –system-site-packages, so it will have access to the installed PyQt4.

To start Orange GUI from the command line, assuming it was successfully installed, run:

orange-canvas # or python3 -m Orange.canvas

Append –help for a list of program options.

If you’re running Orange with PyQt5 or if you have multiple PyQt versions available, set the environmental variable QT_API to the PyQt version to use, e.g.:

export QT_API=pyqt5 orange-canvas

Compiling on Windows

Get appropriate wheels for missing libraries. You will need [numpy+mkl] and [scipy].

[numpy+mkl]: http://www.lfd.uci.edu/~gohlke/pythonlibs/#numpy [scipy]: http://www.lfd.uci.edu/~gohlke/pythonlibs/#scipy

Install them with

pip install some-wheel.whl

Install [Visual Studio compiler]. Then go to Orange3 folder and run:

[Visual Studio compiler]: http://landinghub.visualstudio.com/visual-cpp-build-tools

python setup.py build_ext -i –compiler=msvc install

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  • License: GNU General Public License v3 or later (GPLv3+) (GPLv3+)
  • Author: Bioinformatics Laboratory, FRI UL
  • Tags data mining, machine learning, artificial intelligence
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