Orange – Data Mining Fruitful & Fun
A cross-platform, visual-programming tool for data mining and visualization.
As opposed to most other machine learning / data mining toolkits, Orange can be effectively used by experts and novices alike. It is regularly used by non-programmers like sociologists, psychologists, economists, cognitive scientists, and biomedical researchers who take advantage of easy and intuitive data-flow-based visual programming interface, which supports preparing and preprocessing structured data, various interactive visualizations, building supervised and unsupervised models, clustering, model evaluation, association rules mining, text mining, data fusion, and network analysis.
Orange is one of the best-rated open-source data mining tools with a graphical user interface that can be used by anyone with just basic data mining training.
With over 200 downloads per day, your successful project with Orange will have a wide-reaching effect.
To learn more, read the Wikipedia article on Orange. If you prefer visuals, check out the screenshots, an emerging YouTube channel with video tutorials for absolute beginners, or just download Orange and try it yourself!
Orange – Data Mining Fruitful & Fun 2016 Projects
Primož GodecOrange Add-on: Educational SeriesOur idea is to implement several educational widgets which will be connected in Orange add-on. This widgets will be used for a demonstration of...
sstanovnikOrange.data.Table to pandas migrationThis project is concerned with migrating Orange.data.Table to pandas. This follows the current trend of the programming community of using pandas as...
Salva CarriónRecommender Systems (Add-on)Recommender systems are a crucial component in competitive retail services such Amazon, Netflix or Google. This success is partly due to...
matevzkrenRule induction (CN2)Rule induction from examples is recognised as a fundamental component of many machine learning systems. We propose to implement supervised rule...
AlexeyText Mining Add OnExtend existing add-on by adding/improving widgets.