Data Mining Fruitful and Fun
Open source machine learning and data visualization.
Download Orange 3.36.1
Nov 21, 2023
Scoring Sheet Wizardry: Transforming Data into Insightful Scores
Unveil the capabilities of Orange's Scoring Sheet widgets for transparent, easy-to-interpret machine learning model predictions useful in critical fields where explainability is paramount.
Nov 08, 2023
From Data Portals to Portals of Doom: Avoiding it with Dask
Circumvent the limitations of second-hand data portals: Orange with Dask enables you to process big data sets while ensuring the source's authenticity and enabling custom workflows.
Oct 28, 2023
Can Orange explore a 13 GB data set?
An experimental version of Orange supports much larger data sets. It never loads the whole data set into the working memory; data is only processed in small chunks. We show a case study on a 13 GB spectroscopy data set.
Oct 24, 2023
Dask all Folks: Preparing Large Datasets
Preparing large HDF5 datasets that load into Orange as on-disk data.
Visual Programming
Interactive data exploration for rapid qualitative analysis with clean visualizations. Graphic user interface allows you 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!
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Interactive Data Visualization
Perform simple data analysis with clever data visualization. Explore statistical distributions, box plots and scatter plots, or dive deeper with decision trees, hierarchical clustering, heatmaps, MDS and linear projections. Even your multidimensional data can become sensible in 2D, especially with clever attribute ranking and selections.
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Add-ons Extend Functionality
Use various add-ons available within Orange to mine data from external data sources, perform natural language processing and text mining, conduct network analysis, infer frequent itemset and do association rules mining. Additionally, bioinformaticians and molecular biologists can use Orange to rank genes by their differential expression and perform enrichment analysis. Check out also Orange cousins Single Cell and Quasar.
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Orange users
When teaching data mining, we like to illustrate rather than only explain. And Orange is great at that. Used at schools, universities and in professional training courses across the world, Orange supports hands-on training and visual illustrations of concepts from data science. There are even widgets that were especially designed for teaching.
Learn moreMy laboratory produces large amounts of data from RNA-seq, ChIP-seq and genome resequencing experiments. Orange allows me to analyze my data even though I don’t know how to program. It also allows me to communicate with my collaborators, who are experts in data mining, and with my colleagues and trainees.
Gad Shaulsky, Ph.D.
Molecular biologist and Director of Graduate Studies (Baylor College of Medicine, Houston, USA)
The scientific community is in need of tools that allow easy construction of workflows and visualizations and are capable of analyzing large amounts of data. Orange is a powerful platform to perform data analysis and visualization, see data flow and become more productive. It provides a clean, open source platform and the possibility to add further functionality for all fields of science.
Ferenc Borondics, Ph.D.
Principal beamline scientist at SMIS (SOLEIL synchrotron, France)
I teach Orange workshops monthly to a diverse audience, from undergrad students to expert researchers. Orange is very intuitive, and, by the end of the workshop, the participants are able to perform complex data visualization and basic machine learning analyses. Most of our attendees have been able to incorporate this tool in their research practice.
Francesca Vitali, Ph.D.
Research Assistant Professor (Center for Biomedical Informatics & Biostatistics, The University of Arizona)
Contribute to Orange
If you love using Orange and want to support us, a donation would be very much appreciated. The funds help us fix bugs, implement new features, provide free educational content, and maintain computational infrastructure.
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