By: AJDA, Jul 14, 2017
Orange has a new friend! It’s Miniconda, Anaconda’s little sister. For a long time, the idea was to utilize the friendly nature of Miniconda to install Orange dependencies, which often misbehaved on some platforms. Miniconda provides Orange with Python 3.6 and conda installer, which is then used to handle everything Orange needs for proper functioning. So sssssss-mooth! Miniconda Installer Please know that our Miniconda installer is in a beta state, but we are inviting adventurous testers to try it and report any bugs they find to our issue tracker [there won’t be any of course!
By: AJDA, Apr 14, 2016
Google Summer of Code application period has come to an end. We’ve received 34 applications, some of which were of truly high quality. Now it’s upon us to select the top performing candidates, but before that we wanted to have an overlook of the candidate pool. We’ve gathered data from our Google Form application and gave it a quick view in Orange. First, we needed to preprocess the data a bit, since it came in a messy form of strings.
By: AJDA, Apr 1, 2016
About a week ago we issued an updated stable release of Orange, version 3.3.1. We’ve introduced some new functionalities and improved a few old ones. Here’s what’s new in this release: New widgets: Distance Matrix for visualizing distance measures in a matrix, Distance Transformation for normalization and inversion of distance matrix, Save Distance Matrix and Distance File for saving and loading distances. Last week we also mentioned a really amazing Silhouette Plot, which helps you visually assess cluster quality.
By: AJDA, Nov 27, 2015
Recently we’ve made a short survey that was, upon Orange download, asking people how they found out about Orange, what was their data mining level and where do they work. The main purpose of this is to get a better insight into our user base and to figure out what is the profile of people interested in trying Orange. Here we have some preliminary results that we’ve managed to gather in the past three weeks or so.
By: AJDA, Oct 30, 2015
Ok, we’ve just recently stumbled across an interesting article on how to deal with non normal (non-Gaussian distributed) data. We have an absolutely paranormal data set of 20 persons with weight, height, paleness, vengefulness, habitation and age attributes (download). Let’s check the distribution in Distributions widget. Our first attribute is “Weight” and we see a little hump on the left. Otherwise the data would be normally distributed. Ok, so perhaps we have a few children in the data set.
By: BIOLAB, Jul 3, 2011
Fink packages (we are using for system-wide Orange installations on Mac OS X) were updated to 64-bit. So if you were using 64-bit Fink installation you will be now able also to use Orange (and our binary Fink repository of already compiled packages). Just use this this installation script to configure your local Fink installation to use our binary Fink repository and add information about Orange packages (they are not available among official Fink packages).
By: BIOLAB, Jun 30, 2011
We have updated our daily Debian packages to Squeeze (current Debian stable). You just have to reconfigure our package repository in your /etc/apt/sources.list to: deb http://orange.biolab.si/debian squeeze main deb-src http://orange.biolab.si/debian squeeze main Those packages are compiled for Python 2.6. You can read more about Debian packages in our old blog post.
By: BIOLAB, Mar 4, 2010
We have made still-experimental-but-probably-working Debian repository with daily built Orange packages. Currently without add-ons. To get access to those packages just add those two lines to your /etc/apt/sources.list (this file contains a list of repositories with packages): deb http://orange.biolab.si/debian lenny main deb-src http://orange.biolab.si/debian lenny main And then you can install Orange with this command: aptitude update aptitude install orange-svn Packages are not signed as they are made automatically so you will probably be warned about this.