Data Mining Fruitful and Fun

Open source machine learning and data visualization.

Download Orange 3.36.1

Oct 24, 2023

Dask all Folks: preparing large datasets

Preparing large HDF5 datasets that load into Orange as on-disk data.

Dask all Folks: preparing large datasets

Oct 20, 2023

Recap of 26th International Conference on Discovery Science

Highlighting our papers from the International Conference on Discovery Science

Recap of 26th International Conference on Discovery Science

Oct 17, 2023

Fall Season Brings Fresh Content to the Introduction to Data Science Series

Updates in the Introduction to Data Science Video Series, new video logistic regression nomogram.

Fall Season Brings Fresh Content to the Introduction to Data Science Series

Sep 19, 2023

Why Removing Features Isn't Enough

Find out why merely removing protected attributes will not fix bias. Features often correlate, letting models infer biases. Fairness algorithms are key for genuine bias mitigation.

Why Removing Features Isn't Enough

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.

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My 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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