Orange is a free, open-source data visualization tool that was created for enhanced machine learning and data mining abilities. It features a visual programming front-end for exploratory data analysis and interactive data visualization, and can also be used as a Python library.
This powerful application is designed for both novice or expert programmers alike, who intend to perform data visualization and analysis. The application is packed with features for data analytics and also includes components for machine learning. The utility of the program can be extended through add-ons for bioinformatics and text mining.
How can Orange Help You Create Accurate Data Analysis Using Python Scripting?
Once you have downloaded and install the application following the prompters on your screen, you can then launch the application, set tools and widgets to your preferred settings and the application are ready for use.
Orange consists of a canvas interface where widgets can be placed to create a data analysis workflow. These widgets offer basic functionalities such as selecting features, training predictors, reading the data, showing a data table, visualizing data elements, comparing learning algorithms, and a lot more. The application also enables you to interactively explore visualizations or feed the selected subset into other widgets. Some functions of these utilities and widgets that help in creating data analysis include:
Interactive data visualization: this performs simple data analysis with clever data visualization. It also allows you to explore statistical distributions, hierarchical clustering, box plots and scatter plots, dive deeper with decision trees, heat maps, MDS and linear projections. Your multidimensional data can become workable even in 2D, especially when using the clever attribute ranking and selections.
Visual Programming: this utility enables Interactive data exploration for rapid qualitative analysis with clean visualizations. With its graphic interface, you are able to focus on exploratory data analysis instead of coding, while clever defaults make fast prototyping of a data analysis workflow extremely easy. Place widgets on the canvas, connect them, load your datasets and harvest the insight!
Add-ons Extend Functionality: with its in-built add-ons, you can find a variety available within the application; these add-ons enable you to mine raw data from external data sources, perform natural language processing functions such as text mining, and infer frequent itemset and association rules mining. In addition, bioinformaticians and molecular biologists can find the requisite utilities on the Orange application to rank genes by their differential expression and perform enrichment analysis.
Finally, the application is another great asset for the teaching of data mining, as it comes with a lot of illustrations rather than just mere explanations. Thus it is a great software to have at schools, universities and in professional training courses across the world. The application supports hands-on training and visual illustrations of concepts from data science. It also comes with widgets that are specially designed for teaching.
The application is compatible with Windows Vista, Windows XP, Windows 2000, 2003, Windows 7, 8, and 10 32 and 64-bit computers. It is available for download in a file size of about 67.9 MB
Key Feature of Orange Include:
- Ability to be used without administrative privileges
- Supports visual programming
- Interactive Data Visualization
- It comes with in-built add-ons.
- Canvas support for graphical front-end for data analysis
- Available widgets for data input, data filtering, sampling, imputation, feature manipulation, and feature selection
- Widgets for common visualization
- Supports supervised machine learning algorithms for classification
- Supports supervised machine learning algorithms for regression
- Unsupervised learning algorithms for clustering (k-means, hierarchical clustering) and data projection techniques (multidimensional scaling, principal component analysis, correspondence analysis)
- Provides widgets for frequent mining itemsets
- Supports widgets for working with geospatial data
- Natural language processing and text mining support
- Time series analysis and modelling
Orange is a great component-based data mining software, which includes a wide range of data visualization, exploration, pre-processing and modelling techniques to help you get your data analysis done in one single swoop. It’s nice, and intuitive, user-friendly interface can be used by both novice and expert users. And its use of Python programming language for data mining is an added plus.
We don't have any change log information for Orange 3.23.0 yet. If you have any change log info for this version of Orange you can share with us.
Last Updated: 2019-10-01
Developer: Bioinformatics Laboratory
File size: 452.7 MB
Operating system: Windows 10, Windows 8/8.1, Windows 7, Windows Vista, Windows XP
MD5 Checksum: 2a41521ba2d4f99e4eafcc67e2403d78