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Orange is a component-based visual programming software package for data visualization, machine learning, data mining, and data analysis. Orange components are called widgets. They range from simple data visualization, subset selection, and preprocessing to empirical evaluation of learning algorithms and predictive modeling .
- Orange Data Mining
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Orange is a data mining and visualization toolbox for novice and expert alike. To explore data with Orange, one requires no programming or in-depth mathematical knowledge. We believe that workflow-based data science tools democratize data science by hiding complex underlying mechanics and exposing intuitive concepts. Anyone who owns data, or is mot...
Easy installation
For easy installation, Download the latest released Orange version from our website. To install an add-on, head to Options -> Add-ons... in the menu bar.
Installing with Conda
First, install Miniconda for your OS. Then, create a new conda environment, and install orange3: For installation of an add-on, use: See specific add-on repositories for details.
Installing with pip
We recommend using our standalone installer or conda, but Orange is also installable with pip. You will need a C/C++ compiler (on Windows we suggest using Microsoft Visual Studio Build Tools).
Ensure you've activated the correct virtual environment. If following the above conda instructions:
Run orange-canvas or python3 -m Orange.canvas. Add --help for a list of program options.
The Orange ecosystem
The development of core Orange is primarily split into three repositories: biolab/orange-canvas-core implements the canvas, biolab/orange-widget-base is a handy widget GUI library, biolab/orange3 brings it all together and implements the base data mining toolbox. Additionally, add-ons implement additional widgets for more specific use cases. Anyone can write an add-on. Some of our first-party add-ons: •biolab/orange3-text •biolab/orange3-bioinformatics •biolab/orange3-timeseries •biolab/orange3-single-cell •biolab/orange3-imageanalytics •biolab/orange3-educational •biolab/orange3-geo •biolab/orange3-associate •biolab/orange3-network •biolab/orange3-explain
Setting up for core Orange development
First, fork the repository by pressing the fork button in the top-right corner of this page. Set your GitHub username, create a conda environment, clone your fork, and install it: Now you're ready to work with git. See GitHub's guides on pull requests, forks if you're unfamiliar. If you're having trouble, get in touch on Discord.
Setting up for development of all components
Should you wish to contribute Orange's base components (the widget base and the canvas), you must also clone these two repositories from Github instead of installing them as dependencies of Orange3. First, fork all the repositories to which you want to contribute. Set your GitHub username, create a conda environment, clone your forks, and install them: It's crucial to install orange-base-widget and orange-canvas-core before orange3 to ensure that orange3 will use your local versions.
Interactive visualizations enable exploratory data analysis. One can select interesting data subsets directly from plots, graphs and data tables and mine them in them downstream widgets. For example, select a cluster from the dendrogram of hierarchical clustering and map it to a 2D data presentation in the MDS plot.
Apr 26, 2021 · Orange can be used for unsupervised learning, image analytics, time series analysis, data mining, bioinformatics, etc. Go and try your hands on different functionalities it offers and how it can reduce the task of writing code to no-code for simple yet complex machine learning tasks.
May 4, 2022 · To illustrate how Orange works, here is the simple workflow with the Import Image widget, which loads images and Image Viewer, which shows loaded images. Later in this article, we will show the workflow that embeds images and perform simple analysis.
Aug 6, 2019 · We started off by learning the three ways to setup and install orange into our computer. Then, we explored the user interface and the concept of widget in Orange. Besides, we also tested out three methods to add widget to the canvas.
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Mar 13, 2024 · We also used four research environments - including a new environment we built with Unity called the Construction Lab, where agents need to build sculptures from building blocks which test their object manipulation and intuitive understanding of the physical world.
