Orange Blog
By: BIOLAB, Oct 26, 2011
GSoC Mentor Summit
On 22th and 23th October 2011 there was Google Summer of Code Mentor Summit in Mountain View, California. Google Summer of Code is Google’s program for encouraging students to work on open-source projects during their summer break. Because this year Orange participated in this program too, we decided to participate also in this summit and get to know other mentors, other open-source projects and organizations, exchange our experiences, learn something new, and improve our connections and collaborations with others.
By: BIOLAB, Sep 13, 2011
Debian packages support multiple Python versions now
We have created Debian packages for multiple Python versions. This means that they work now with both Python 2.6 and 2.7 out of the box, or if you compile them manually, with any (supported) version you have installed on your (Debian-based) system. Practically, this means that now you can install them without manual compiling on current Debian and Ubuntu systems. Give it a try, add our Debian package repository, apt-get install python-orange for Orange library/modules and/or orange-canvas for GUI.
By: BIOLAB, Sep 7, 2011
3D Visualizations in Orange
Over the summer I worked (and still do) on several new 3D visualization widgets as well as a 3D plotting library they use, which will hopefully simplify making more widgets. The library is designed to be similar in terms of API to the new Qt plotting library Noughmad is working on. The library uses OpenGL 2/3: since Khronos deprecated parts of the old OpenGL API (particularly immediate mode and fixed-function functionality) care has been taken to use only capabilities less likely to go away in the years to come.
By: BIOLAB, Sep 4, 2011
Orange badges are here!
Orange badges are here! They come in two flavors. Tasty!
By: BIOLAB, Sep 3, 2011
GSoC Review: Visualizations with Qt
During the course of this summer, I created a new plotting library for Orange plot, replacing the use of PyQwt. I can say that I have succesfully completed my project, but the library (and especially the visualization widgets) could still use some more work. The new library supports a similar interface, so little change is needed to convert individual widgets, but it also has several advantages over the old implementation:
By: BIOLAB, Sep 2, 2011
GSoC Review: Multi-label Classification Implementation
Traditional single-label classification is concerned with learning from a set of examples that are associated with a single label l from a set of disjoint labels L, |L| > 1. If |L| = 2, then the learning problem is called a binary classification problem, while if |L| > 2, then it is called a multi-class classification problem (Tsoumakas & Katakis, 2007). Multi-label classification methods are increasingly used by many applications, such as textual data classification, protein function classification, music categorization and semantic scene classification.
By: BIOLAB, Sep 1, 2011
GSoC Review: MF - Matrix Factorization Techniques for Data Mining
MF - Matrix Factorization Techniques for Data Mining is a Python scripting library which includes a number of published matrix factorization algorithms, initialization methods, quality and performance measures and facilitates the combination of these to produce new strategies. The library represents a unified and efficient interface to matrix factorization algorithms and methods. The MF works with numpy dense matrices and scipy sparse matrices (where this is possible to save on space).
By: BIOLAB, Aug 24, 2011
Faster classification and regression trees
SimpleTreeLearner is an implementation of classification and regression trees that sacrifices flexibility for speed. A benchmark on 42 different datasets reveals that SimpleTreeLearner is 11 times faster than the original TreeLearner. The motivation behind developing a new tree induction algorithm from scratch was to speed up the construction of random forests, but you can also use it as a standalone learner. SimpleTreeLearner uses gain ratio for classification and MSE for regression and can handle unknown values.
By: MARKO, Aug 19, 2011
Golden (sublime) triangles in Orange
Hand in hand with the development of the new visualization framework and the financial crisis we are putting some gold into Orange. The arrows at the ends of the axes are, as of today, small golden triangles. See the changes in owaxis.py! - path.moveTo(0, 3) - path.lineTo(0, -3) - path.lineTo(5, 0) + path.moveTo(0, 3.09) + path.lineTo(0, -3.09) + path.lineTo(9.51, 0)
By: MARKO, Aug 3, 2011
Orange at ISMB/ECCB 2011
We presented the Orange Bioinformatics add-on at the ISMB/ECCB conference in Vienna, a joined event covering both 19th Annual International Conference on Intelligent Systems for Molecular Biology and 10th European Conference on Computational Biology. We were giving out Orange stickers (with the URL) to the poster’s visitors. There was some interest; in the end we gave out about 10 of them, mostly to biologists, who were excited to perform some of the analysis themselves.